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      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\Krause & Park.Authority Differentials.APPENDIX E RESULTS.08-07-2024.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 7 Aug 2024, 15:49:58
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. ***** SUPPLEMENTARY APPENDIX STATISTICAL ANALYSES:  APPENDIX E: REPLICATION ANALYSES USING ORGANIZATIONAL JUSTICE LATENT VARIABLE /// ***
> ***** AS ALTERNATIVE DEPENDENT VARIABLE (CONVERGENT & CONTENT VALIDITY) ******
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. *** ACCESS DATABASE FOR THE PROJECT: FEVS DATA FROM 2010-2019 AND 'MATCHED' OPM DATA ****
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. *** 2. CONDITIONAL-RESPONDENT MODELS EVALUATING THE RELATIONSHIP INVOLVING WITHIN-IDENTITY "OUT-GROUP" STATUS & BETWEEN-IDENTITY GROUP STATUS DIFFERENTIALS AS A MEANS TO FOSTER DIVERSITY AND INCLUSION IN THE U.S. CIVILIAN WORKFORCE ***   
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. *** MODEL E1: CONDITIONAL RESPONSES BY GENDER -- GENDER BETWEEN-IDENTITY GROUP STATUS DIFFERENTIAL MODEL: [WOMEN SUPERVISORS WITHIN AGENCY j IN YEAR t / MEN SUPERVISORS WITHIN AGENCY j IN YEAR t] / [WOMEN NON-SUPERVISORS WITHIN AGENCY j IN YEAR t / MEN NON-SUPERVISORS  WITHIN AGENCY j IN YEAR t]  -- CONTROLLING FOR GENDER SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL ***
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. regress lnjustice2zeroadj   c.ln_ratio_fmsup_fmsub##i.gender   ln_ratio_fem_tot_men_tot  minority  supervisor  topoffgender_2 lntotworkforce_count  ln_professionals_total_ratio   i.agencyid i.year, vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(17, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0480
                                                {txt}Root MSE          =    {res} .52092

{txt}{ralign 95:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}            lnjustice2zeroadj{col 31}{c |} Coefficient{col 43}  std. err.{col 55}      t{col 63}   P>|t|{col 71}     [95% con{col 84}f. interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}ln_ratio_fmsup_fmsub {c |}{col 31}{res}{space 2} .1318043{col 43}{space 2}  .047331{col 54}{space 1}    2.78{col 63}{space 3}0.006{col 71}{space 4}  .037945{col 84}{space 3} .2256635
{txt}{space 21}1.gender {c |}{col 31}{res}{space 2}-.0285501{col 43}{space 2}   .00776{col 54}{space 1}   -3.68{col 63}{space 3}0.000{col 71}{space 4}-.0439385{col 84}{space 3}-.0131617
{txt}{space 29} {c |}
gender#c.ln_ratio_fmsup_fmsub {c |}
{space 27}1  {c |}{col 31}{res}{space 2} .0044466{col 43}{space 2} .0211248{col 54}{space 1}    0.21{col 63}{space 3}0.834{col 71}{space 4}-.0374446{col 84}{space 3} .0463378
{txt}{space 29} {c |}
{space 5}ln_ratio_fem_tot_men_tot {c |}{col 31}{res}{space 2}-.0258781{col 43}{space 2}  .065312{col 54}{space 1}   -0.40{col 63}{space 3}0.693{col 71}{space 4}-.1553943{col 84}{space 3} .1036381
{txt}{space 21}minority {c |}{col 31}{res}{space 2}-.0524303{col 43}{space 2} .0037426{col 54}{space 1}  -14.01{col 63}{space 3}0.000{col 71}{space 4} -.059852{col 84}{space 3}-.0450086
{txt}{space 19}supervisor {c |}{col 31}{res}{space 2} .1656805{col 43}{space 2} .0079443{col 54}{space 1}   20.86{col 63}{space 3}0.000{col 71}{space 4} .1499266{col 84}{space 3} .1814344
{txt}{space 15}topoffgender_2 {c |}{col 31}{res}{space 2}-.0049881{col 43}{space 2} .0051658{col 54}{space 1}   -0.97{col 63}{space 3}0.336{col 71}{space 4}-.0152321{col 84}{space 3}  .005256
{txt}{space 9}lntotworkforce_count {c |}{col 31}{res}{space 2} .0713789{col 43}{space 2} .0340411{col 54}{space 1}    2.10{col 63}{space 3}0.038{col 71}{space 4}  .003874{col 84}{space 3} .1388838
{txt}{space 1}ln_professionals_total_ratio {c |}{col 31}{res}{space 2}  .017229{col 43}{space 2} .0441638{col 54}{space 1}    0.39{col 63}{space 3}0.697{col 71}{space 4}-.0703494{col 84}{space 3} .1048074
{txt}{space 29} {c |}
{space 21}agencyid {c |}
{space 27}2  {c |}{col 31}{res}{space 2} .2872377{col 43}{space 2}  .117856{col 54}{space 1}    2.44{col 63}{space 3}0.016{col 71}{space 4} .0535248{col 84}{space 3} .5209507
{txt}{space 27}3  {c |}{col 31}{res}{space 2} .0281481{col 43}{space 2}  .055633{col 54}{space 1}    0.51{col 63}{space 3}0.614{col 71}{space 4}-.0821742{col 84}{space 3} .1384703
{txt}{space 27}4  {c |}{col 31}{res}{space 2} .3920446{col 43}{space 2} .1582549{col 54}{space 1}    2.48{col 63}{space 3}0.015{col 71}{space 4} .0782192{col 84}{space 3} .7058701
{txt}{space 27}5  {c |}{col 31}{res}{space 2} .2425277{col 43}{space 2} .1083259{col 54}{space 1}    2.24{col 63}{space 3}0.027{col 71}{space 4} .0277135{col 84}{space 3}  .457342
{txt}{space 27}6  {c |}{col 31}{res}{space 2} .2006883{col 43}{space 2}  .114423{col 54}{space 1}    1.75{col 63}{space 3}0.082{col 71}{space 4}-.0262168{col 84}{space 3} .4275934
{txt}{space 27}7  {c |}{col 31}{res}{space 2} .3234453{col 43}{space 2} .1898653{col 54}{space 1}    1.70{col 63}{space 3}0.091{col 71}{space 4}-.0530648{col 84}{space 3} .6999553
{txt}{space 27}8  {c |}{col 31}{res}{space 2} .2720632{col 43}{space 2} .1475457{col 54}{space 1}    1.84{col 63}{space 3}0.068{col 71}{space 4}-.0205254{col 84}{space 3} .5646518
{txt}{space 27}9  {c |}{col 31}{res}{space 2}-.0111336{col 43}{space 2} .0266301{col 54}{space 1}   -0.42{col 63}{space 3}0.677{col 71}{space 4}-.0639421{col 84}{space 3} .0416749
{txt}{space 26}10  {c |}{col 31}{res}{space 2} .1995228{col 43}{space 2} .1696506{col 54}{space 1}    1.18{col 63}{space 3}0.242{col 71}{space 4}-.1369007{col 84}{space 3} .5359462
{txt}{space 26}11  {c |}{col 31}{res}{space 2}  .208802{col 43}{space 2} .1268693{col 54}{space 1}    1.65{col 63}{space 3}0.103{col 71}{space 4}-.0427847{col 84}{space 3} .4603886
{txt}{space 26}12  {c |}{col 31}{res}{space 2} .4029783{col 43}{space 2} .1789676{col 54}{space 1}    2.25{col 63}{space 3}0.026{col 71}{space 4} .0480788{col 84}{space 3} .7578777
{txt}{space 26}13  {c |}{col 31}{res}{space 2}  .365843{col 43}{space 2} .1491116{col 54}{space 1}    2.45{col 63}{space 3}0.016{col 71}{space 4} .0701491{col 84}{space 3}  .661537
{txt}{space 26}14  {c |}{col 31}{res}{space 2} .1828679{col 43}{space 2} .1097595{col 54}{space 1}    1.67{col 63}{space 3}0.099{col 71}{space 4}-.0347894{col 84}{space 3} .4005252
{txt}{space 26}15  {c |}{col 31}{res}{space 2} .3298724{col 43}{space 2} .1208291{col 54}{space 1}    2.73{col 63}{space 3}0.007{col 71}{space 4} .0902637{col 84}{space 3}  .569481
{txt}{space 26}16  {c |}{col 31}{res}{space 2} .4054179{col 43}{space 2} .2036526{col 54}{space 1}    1.99{col 63}{space 3}0.049{col 71}{space 4} .0015671{col 84}{space 3} .8092686
{txt}{space 26}17  {c |}{col 31}{res}{space 2} .1288736{col 43}{space 2} .1697513{col 54}{space 1}    0.76{col 63}{space 3}0.449{col 71}{space 4}-.2077495{col 84}{space 3} .4654968
{txt}{space 26}18  {c |}{col 31}{res}{space 2} .3385514{col 43}{space 2} .1576087{col 54}{space 1}    2.15{col 63}{space 3}0.034{col 71}{space 4} .0260076{col 84}{space 3} .6510953
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{txt}{space 26}21  {c |}{col 31}{res}{space 2} .2591595{col 43}{space 2} .1259992{col 54}{space 1}    2.06{col 63}{space 3}0.042{col 71}{space 4} .0092983{col 84}{space 3} .5090207
{txt}{space 26}22  {c |}{col 31}{res}{space 2} .2727704{col 43}{space 2} .1485312{col 54}{space 1}    1.84{col 63}{space 3}0.069{col 71}{space 4}-.0217725{col 84}{space 3} .5673134
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{txt}{space 26}24  {c |}{col 31}{res}{space 2} .2934245{col 43}{space 2}  .100427{col 54}{space 1}    2.92{col 63}{space 3}0.004{col 71}{space 4}  .094274{col 84}{space 3} .4925749
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{txt}{space 26}34  {c |}{col 31}{res}{space 2}   .12834{col 43}{space 2} .1247074{col 54}{space 1}    1.03{col 63}{space 3}0.306{col 71}{space 4}-.1189595{col 84}{space 3} .3756395
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{txt}{space 26}44  {c |}{col 31}{res}{space 2} .3456619{col 43}{space 2} .1079439{col 54}{space 1}    3.20{col 63}{space 3}0.002{col 71}{space 4}  .131605{col 84}{space 3} .5597187
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{txt}{space 26}46  {c |}{col 31}{res}{space 2} .2920807{col 43}{space 2} .1946798{col 54}{space 1}    1.50{col 63}{space 3}0.137{col 71}{space 4}-.0939767{col 84}{space 3} .6781381
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{txt}{space 26}79  {c |}{col 31}{res}{space 2}-.0203566{col 43}{space 2} .0175407{col 54}{space 1}   -1.16{col 63}{space 3}0.248{col 71}{space 4}-.0551404{col 84}{space 3} .0144272
{txt}{space 26}80  {c |}{col 31}{res}{space 2} .4333361{col 43}{space 2} .1810585{col 54}{space 1}    2.39{col 63}{space 3}0.018{col 71}{space 4} .0742902{col 84}{space 3}  .792382
{txt}{space 26}81  {c |}{col 31}{res}{space 2} .2380573{col 43}{space 2} .1854042{col 54}{space 1}    1.28{col 63}{space 3}0.202{col 71}{space 4}-.1296061{col 84}{space 3} .6057207
{txt}{space 26}82  {c |}{col 31}{res}{space 2} .3367496{col 43}{space 2} .1907708{col 54}{space 1}    1.77{col 63}{space 3}0.080{col 71}{space 4}-.0415561{col 84}{space 3} .7150553
{txt}{space 26}83  {c |}{col 31}{res}{space 2} .4005676{col 43}{space 2} .1503548{col 54}{space 1}    2.66{col 63}{space 3}0.009{col 71}{space 4} .1024084{col 84}{space 3} .6987267
{txt}{space 26}84  {c |}{col 31}{res}{space 2} .3565403{col 43}{space 2} .1915576{col 54}{space 1}    1.86{col 63}{space 3}0.066{col 71}{space 4}-.0233257{col 84}{space 3} .7364062
{txt}{space 26}85  {c |}{col 31}{res}{space 2} .4360083{col 43}{space 2} .1553717{col 54}{space 1}    2.81{col 63}{space 3}0.006{col 71}{space 4} .1279003{col 84}{space 3} .7441163
{txt}{space 26}86  {c |}{col 31}{res}{space 2} .4312836{col 43}{space 2}  .195965{col 54}{space 1}    2.20{col 63}{space 3}0.030{col 71}{space 4} .0426777{col 84}{space 3} .8198894
{txt}{space 26}87  {c |}{col 31}{res}{space 2} .4863881{col 43}{space 2} .1990566{col 54}{space 1}    2.44{col 63}{space 3}0.016{col 71}{space 4} .0916514{col 84}{space 3} .8811248
{txt}{space 26}88  {c |}{col 31}{res}{space 2} .2388347{col 43}{space 2} .1412339{col 54}{space 1}    1.69{col 63}{space 3}0.094{col 71}{space 4}-.0412374{col 84}{space 3} .5189068
{txt}{space 26}89  {c |}{col 31}{res}{space 2} .2748072{col 43}{space 2} .1504889{col 54}{space 1}    1.83{col 63}{space 3}0.071{col 71}{space 4} -.023618{col 84}{space 3} .5732325
{txt}{space 26}90  {c |}{col 31}{res}{space 2} .0975986{col 43}{space 2} .1228631{col 54}{space 1}    0.79{col 63}{space 3}0.429{col 71}{space 4}-.1460435{col 84}{space 3} .3412407
{txt}{space 26}91  {c |}{col 31}{res}{space 2}  .190457{col 43}{space 2} .1142035{col 54}{space 1}    1.67{col 63}{space 3}0.098{col 71}{space 4}-.0360129{col 84}{space 3} .4169269
{txt}{space 26}92  {c |}{col 31}{res}{space 2} .0808079{col 43}{space 2}  .048838{col 54}{space 1}    1.65{col 63}{space 3}0.101{col 71}{space 4}-.0160397{col 84}{space 3} .1776555
{txt}{space 26}93  {c |}{col 31}{res}{space 2}  .418293{col 43}{space 2}  .151732{col 54}{space 1}    2.76{col 63}{space 3}0.007{col 71}{space 4} .1174028{col 84}{space 3} .7191832
{txt}{space 26}94  {c |}{col 31}{res}{space 2} .4420155{col 43}{space 2} .1768535{col 54}{space 1}    2.50{col 63}{space 3}0.014{col 71}{space 4} .0913084{col 84}{space 3} .7927225
{txt}{space 26}95  {c |}{col 31}{res}{space 2} .1692044{col 43}{space 2} .1541311{col 54}{space 1}    1.10{col 63}{space 3}0.275{col 71}{space 4}-.1364433{col 84}{space 3} .4748521
{txt}{space 26}96  {c |}{col 31}{res}{space 2}  .355573{col 43}{space 2} .1596977{col 54}{space 1}    2.23{col 63}{space 3}0.028{col 71}{space 4} .0388865{col 84}{space 3} .6722595
{txt}{space 26}97  {c |}{col 31}{res}{space 2} .3981784{col 43}{space 2}  .154556{col 54}{space 1}    2.58{col 63}{space 3}0.011{col 71}{space 4}  .091688{col 84}{space 3} .7046688
{txt}{space 26}98  {c |}{col 31}{res}{space 2} .5537984{col 43}{space 2} .1905639{col 54}{space 1}    2.91{col 63}{space 3}0.004{col 71}{space 4} .1759031{col 84}{space 3} .9316937
{txt}{space 26}99  {c |}{col 31}{res}{space 2} .1218751{col 43}{space 2} .1043442{col 54}{space 1}    1.17{col 63}{space 3}0.245{col 71}{space 4}-.0850434{col 84}{space 3} .3287937
{txt}{space 25}100  {c |}{col 31}{res}{space 2} .2022085{col 43}{space 2}  .156758{col 54}{space 1}    1.29{col 63}{space 3}0.200{col 71}{space 4}-.1086484{col 84}{space 3} .5130655
{txt}{space 25}101  {c |}{col 31}{res}{space 2}  .416328{col 43}{space 2} .1399504{col 54}{space 1}    2.97{col 63}{space 3}0.004{col 71}{space 4}  .138801{col 84}{space 3}  .693855
{txt}{space 25}102  {c |}{col 31}{res}{space 2} .2763962{col 43}{space 2} .1646462{col 54}{space 1}    1.68{col 63}{space 3}0.096{col 71}{space 4}-.0501033{col 84}{space 3} .6028958
{txt}{space 25}103  {c |}{col 31}{res}{space 2} .0898027{col 43}{space 2} .1129755{col 54}{space 1}    0.79{col 63}{space 3}0.428{col 71}{space 4}-.1342319{col 84}{space 3} .3138374
{txt}{space 25}104  {c |}{col 31}{res}{space 2}-.0982744{col 43}{space 2} .0892256{col 54}{space 1}   -1.10{col 63}{space 3}0.273{col 71}{space 4}-.2752121{col 84}{space 3} .0786633
{txt}{space 25}105  {c |}{col 31}{res}{space 2} .3344501{col 43}{space 2} .1586728{col 54}{space 1}    2.11{col 63}{space 3}0.037{col 71}{space 4}  .019796{col 84}{space 3} .6491043
{txt}{space 29} {c |}
{space 25}year {c |}
{space 24}2011  {c |}{col 31}{res}{space 2}-.0030751{col 43}{space 2} .0033498{col 54}{space 1}   -0.92{col 63}{space 3}0.361{col 71}{space 4}-.0097178{col 84}{space 3} .0035677
{txt}{space 24}2012  {c |}{col 31}{res}{space 2} .0072932{col 43}{space 2} .0052899{col 54}{space 1}    1.38{col 63}{space 3}0.171{col 71}{space 4}-.0031969{col 84}{space 3} .0177834
{txt}{space 24}2013  {c |}{col 31}{res}{space 2} .0099739{col 43}{space 2}  .005945{col 54}{space 1}    1.68{col 63}{space 3}0.096{col 71}{space 4}-.0018152{col 84}{space 3} .0217631
{txt}{space 24}2014  {c |}{col 31}{res}{space 2} .0093117{col 43}{space 2} .0080879{col 54}{space 1}    1.15{col 63}{space 3}0.252{col 71}{space 4} -.006727{col 84}{space 3} .0253504
{txt}{space 24}2015  {c |}{col 31}{res}{space 2} .0036888{col 43}{space 2} .0096595{col 54}{space 1}    0.38{col 63}{space 3}0.703{col 71}{space 4}-.0154664{col 84}{space 3}  .022844
{txt}{space 24}2016  {c |}{col 31}{res}{space 2} .0014301{col 43}{space 2} .0082456{col 54}{space 1}    0.17{col 63}{space 3}0.863{col 71}{space 4}-.0149213{col 84}{space 3} .0177815
{txt}{space 24}2017  {c |}{col 31}{res}{space 2} .0091375{col 43}{space 2} .0111837{col 54}{space 1}    0.82{col 63}{space 3}0.416{col 71}{space 4}-.0130402{col 84}{space 3} .0313153
{txt}{space 24}2018  {c |}{col 31}{res}{space 2}-.0210228{col 43}{space 2} .0088835{col 54}{space 1}   -2.37{col 63}{space 3}0.020{col 71}{space 4}-.0386393{col 84}{space 3}-.0034064
{txt}{space 24}2019  {c |}{col 31}{res}{space 2}-.0515611{col 43}{space 2} .0098933{col 54}{space 1}   -5.21{col 63}{space 3}0.000{col 71}{space 4}-.0711798{col 84}{space 3}-.0319424
{txt}{space 29} {c |}
{space 24}_cons {c |}{col 31}{res}{space 2} .0390323{col 43}{space 2} .4325011{col 54}{space 1}    0.09{col 63}{space 3}0.928{col 71}{space 4}-.8186335{col 84}{space 3} .8966981
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1984008{col 39} -1922333{col 50}    18{col 58}  3844701{col 69}  3844931
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. ** BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN GENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1318043{col 26}{space 2}  .047331{col 37}{space 1}    2.78{col 46}{space 3}0.006{col 54}{space 4}  .037945{col 67}{space 3} .2256635
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.gender#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.gender#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0044466{col 26}{space 2} .0211248{col 37}{space 1}    0.21{col 46}{space 3}0.834{col 54}{space 4}-.0374446{col 67}{space 3} .0463378
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. 
.    
. *** MODEL E2: CONDITIONAL RESPONSES BY RACE/ETHNICITY -- RACIAL/ETHNIC BETWEEN-IDENTITY GROUP STATUS DIFFERENTIAL MODEL: [MINORITY SUPERVISORS WITHIN AGENCY j IN YEAR t / NON-MINORITY SUPERVISORS WITHIN AGENCY j IN YEAR t] / [MINORITY NON-SUPERVISORS WITHIN AGENCY j IN YEAR t / NON-MINORITY NON-SUPERVISORS  WITHIN AGENCY j IN YEAR t] -- CONTROLLING FOR RACIAL/ETHNIC SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL ***
. 
. regress  lnjustice2zeroadj   c.ln_ratio_mnmsup_mnmsub##i.minority   ln_ratio_min_tot_nmin_tot   gender supervisor  topoffminority_2 lntotworkforce_count  ln_professionals_total_ratio   i.agencyid i.year, vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(17, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0480
                                                {txt}Root MSE          =    {res} .52093

{txt}{ralign 99:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 34}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 35}{c |}{col 47}    Robust
{col 1}                lnjustice2zeroadj{col 35}{c |} Coefficient{col 47}  std. err.{col 59}      t{col 67}   P>|t|{col 75}     [95% con{col 88}f. interval]
{hline 34}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}ln_ratio_mnmsup_mnmsub {c |}{col 35}{res}{space 2} .0540032{col 47}{space 2} .0351111{col 58}{space 1}    1.54{col 67}{space 3}0.127{col 75}{space 4}-.0156235{col 88}{space 3} .1236299
{txt}{space 23}1.minority {c |}{col 35}{res}{space 2}-.0351633{col 47}{space 2} .0068791{col 58}{space 1}   -5.11{col 67}{space 3}0.000{col 75}{space 4}-.0488048{col 88}{space 3}-.0215219
{txt}{space 33} {c |}
minority#c.ln_ratio_mnmsup_mnmsub {c |}
{space 31}1  {c |}{col 35}{res}{space 2} .0499643{col 47}{space 2} .0179561{col 58}{space 1}    2.78{col 67}{space 3}0.006{col 75}{space 4} .0143566{col 88}{space 3} .0855721
{txt}{space 33} {c |}
{space 8}ln_ratio_min_tot_nmin_tot {c |}{col 35}{res}{space 2} .0230165{col 47}{space 2} .0499788{col 58}{space 1}    0.46{col 67}{space 3}0.646{col 75}{space 4}-.0760933{col 88}{space 3} .1221263
{txt}{space 27}gender {c |}{col 35}{res}{space 2}-.0301021{col 47}{space 2} .0045588{col 58}{space 1}   -6.60{col 67}{space 3}0.000{col 75}{space 4}-.0391424{col 88}{space 3}-.0210618
{txt}{space 23}supervisor {c |}{col 35}{res}{space 2} .1657048{col 47}{space 2} .0079319{col 58}{space 1}   20.89{col 67}{space 3}0.000{col 75}{space 4} .1499755{col 88}{space 3} .1814341
{txt}{space 17}topoffminority_2 {c |}{col 35}{res}{space 2} .0071833{col 47}{space 2} .0071604{col 58}{space 1}    1.00{col 67}{space 3}0.318{col 75}{space 4} -.007016{col 88}{space 3} .0213826
{txt}{space 13}lntotworkforce_count {c |}{col 35}{res}{space 2} .0641981{col 47}{space 2} .0408755{col 58}{space 1}    1.57{col 67}{space 3}0.119{col 75}{space 4}-.0168596{col 88}{space 3} .1452559
{txt}{space 5}ln_professionals_total_ratio {c |}{col 35}{res}{space 2} .0253154{col 47}{space 2} .0499736{col 58}{space 1}    0.51{col 67}{space 3}0.614{col 75}{space 4}-.0737842{col 88}{space 3}  .124415
{txt}{space 33} {c |}
{space 25}agencyid {c |}
{space 31}2  {c |}{col 35}{res}{space 2} .1948107{col 47}{space 2} .1270576{col 58}{space 1}    1.53{col 67}{space 3}0.128{col 75}{space 4}-.0571492{col 88}{space 3} .4467706
{txt}{space 31}3  {c |}{col 35}{res}{space 2} -.041902{col 47}{space 2} .0571216{col 58}{space 1}   -0.73{col 67}{space 3}0.465{col 75}{space 4}-.1551764{col 88}{space 3} .0713723
{txt}{space 31}4  {c |}{col 35}{res}{space 2} .2293531{col 47}{space 2} .1640228{col 58}{space 1}    1.40{col 67}{space 3}0.165{col 75}{space 4}-.0959103{col 88}{space 3} .5546166
{txt}{space 31}5  {c |}{col 35}{res}{space 2} .1627549{col 47}{space 2}  .127553{col 58}{space 1}    1.28{col 67}{space 3}0.205{col 75}{space 4}-.0901876{col 88}{space 3} .4156973
{txt}{space 31}6  {c |}{col 35}{res}{space 2} .1212419{col 47}{space 2} .1231504{col 58}{space 1}    0.98{col 67}{space 3}0.327{col 75}{space 4}-.1229699{col 88}{space 3} .3654538
{txt}{space 31}7  {c |}{col 35}{res}{space 2} .2333517{col 47}{space 2} .2160929{col 58}{space 1}    1.08{col 67}{space 3}0.283{col 75}{space 4}-.1951686{col 88}{space 3}  .661872
{txt}{space 31}8  {c |}{col 35}{res}{space 2} .2115111{col 47}{space 2} .1648737{col 58}{space 1}    1.28{col 67}{space 3}0.202{col 75}{space 4}-.1154397{col 88}{space 3} .5384619
{txt}{space 31}9  {c |}{col 35}{res}{space 2}-.0501321{col 47}{space 2} .0239705{col 58}{space 1}   -2.09{col 67}{space 3}0.039{col 75}{space 4}-.0976665{col 88}{space 3}-.0025977
{txt}{space 30}10  {c |}{col 35}{res}{space 2} .1687374{col 47}{space 2} .2259128{col 58}{space 1}    0.75{col 67}{space 3}0.457{col 75}{space 4}-.2792562{col 88}{space 3}  .616731
{txt}{space 30}11  {c |}{col 35}{res}{space 2} .1425878{col 47}{space 2} .1037931{col 58}{space 1}    1.37{col 67}{space 3}0.172{col 75}{space 4}-.0632377{col 88}{space 3} .3484133
{txt}{space 30}12  {c |}{col 35}{res}{space 2} .3427388{col 47}{space 2} .2133776{col 58}{space 1}    1.61{col 67}{space 3}0.111{col 75}{space 4} -.080397{col 88}{space 3} .7658745
{txt}{space 30}13  {c |}{col 35}{res}{space 2} .3326235{col 47}{space 2}  .170019{col 58}{space 1}    1.96{col 67}{space 3}0.053{col 75}{space 4}-.0045306{col 88}{space 3} .6697776
{txt}{space 30}14  {c |}{col 35}{res}{space 2} .1711933{col 47}{space 2} .1175042{col 58}{space 1}    1.46{col 67}{space 3}0.148{col 75}{space 4} -.061822{col 88}{space 3} .4042086
{txt}{space 30}15  {c |}{col 35}{res}{space 2} .3010697{col 47}{space 2}  .157107{col 58}{space 1}    1.92{col 67}{space 3}0.058{col 75}{space 4}-.0104794{col 88}{space 3} .6126188
{txt}{space 30}16  {c |}{col 35}{res}{space 2} .2252656{col 47}{space 2} .2905552{col 58}{space 1}    0.78{col 67}{space 3}0.440{col 75}{space 4}-.3509163{col 88}{space 3} .8014476
{txt}{space 30}17  {c |}{col 35}{res}{space 2} .0506164{col 47}{space 2} .1823507{col 58}{space 1}    0.28{col 67}{space 3}0.782{col 75}{space 4}-.3109919{col 88}{space 3} .4122247
{txt}{space 30}18  {c |}{col 35}{res}{space 2} .3043231{col 47}{space 2} .1739513{col 58}{space 1}    1.75{col 67}{space 3}0.083{col 75}{space 4}-.0406288{col 88}{space 3} .6492751
{txt}{space 30}19  {c |}{col 35}{res}{space 2} .1763651{col 47}{space 2} .1176174{col 58}{space 1}    1.50{col 67}{space 3}0.137{col 75}{space 4}-.0568747{col 88}{space 3} .4096048
{txt}{space 30}20  {c |}{col 35}{res}{space 2} .0209127{col 47}{space 2} .1241211{col 58}{space 1}    0.17{col 67}{space 3}0.867{col 75}{space 4}-.2252242{col 88}{space 3} .2670496
{txt}{space 30}21  {c |}{col 35}{res}{space 2} .1876201{col 47}{space 2} .1105975{col 58}{space 1}    1.70{col 67}{space 3}0.093{col 75}{space 4} -.031699{col 88}{space 3} .4069392
{txt}{space 30}22  {c |}{col 35}{res}{space 2} .1767056{col 47}{space 2}  .174919{col 58}{space 1}    1.01{col 67}{space 3}0.315{col 75}{space 4}-.1701653{col 88}{space 3} .5235765
{txt}{space 30}23  {c |}{col 35}{res}{space 2}-.1100972{col 47}{space 2} .0870503{col 58}{space 1}   -1.26{col 67}{space 3}0.209{col 75}{space 4}-.2827213{col 88}{space 3} .0625269
{txt}{space 30}24  {c |}{col 35}{res}{space 2} .2600924{col 47}{space 2} .1235022{col 58}{space 1}    2.11{col 67}{space 3}0.038{col 75}{space 4} .0151829{col 88}{space 3} .5050018
{txt}{space 30}25  {c |}{col 35}{res}{space 2} .1813095{col 47}{space 2} .1439595{col 58}{space 1}    1.26{col 67}{space 3}0.211{col 75}{space 4}-.1041675{col 88}{space 3} .4667865
{txt}{space 30}26  {c |}{col 35}{res}{space 2} .0348562{col 47}{space 2} .1275013{col 58}{space 1}    0.27{col 67}{space 3}0.785{col 75}{space 4}-.2179837{col 88}{space 3} .2876961
{txt}{space 30}27  {c |}{col 35}{res}{space 2} .2738129{col 47}{space 2} .2006634{col 58}{space 1}    1.36{col 67}{space 3}0.175{col 75}{space 4}-.1241102{col 88}{space 3}  .671736
{txt}{space 30}28  {c |}{col 35}{res}{space 2} -.070354{col 47}{space 2} .1087278{col 58}{space 1}   -0.65{col 67}{space 3}0.519{col 75}{space 4}-.2859653{col 88}{space 3} .1452573
{txt}{space 30}29  {c |}{col 35}{res}{space 2} .0721209{col 47}{space 2} .1838537{col 58}{space 1}    0.39{col 67}{space 3}0.696{col 75}{space 4}-.2924678{col 88}{space 3} .4367096
{txt}{space 30}30  {c |}{col 35}{res}{space 2}  .110666{col 47}{space 2} .1689054{col 58}{space 1}    0.66{col 67}{space 3}0.514{col 75}{space 4}-.2242798{col 88}{space 3} .4456118
{txt}{space 30}31  {c |}{col 35}{res}{space 2}-.0833511{col 47}{space 2} .1761789{col 58}{space 1}   -0.47{col 67}{space 3}0.637{col 75}{space 4}-.4327204{col 88}{space 3} .2660182
{txt}{space 30}32  {c |}{col 35}{res}{space 2} .2071349{col 47}{space 2} .1430738{col 58}{space 1}    1.45{col 67}{space 3}0.151{col 75}{space 4}-.0765858{col 88}{space 3} .4908556
{txt}{space 30}33  {c |}{col 35}{res}{space 2} .1194908{col 47}{space 2}  .088972{col 58}{space 1}    1.34{col 67}{space 3}0.182{col 75}{space 4} -.056944{col 88}{space 3} .2959256
{txt}{space 30}34  {c |}{col 35}{res}{space 2}-.0695348{col 47}{space 2} .2327588{col 58}{space 1}   -0.30{col 67}{space 3}0.766{col 75}{space 4}-.5311041{col 88}{space 3} .3920346
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{txt}{space 30}36  {c |}{col 35}{res}{space 2} .1840854{col 47}{space 2} .1405435{col 58}{space 1}    1.31{col 67}{space 3}0.193{col 75}{space 4}-.0946176{col 88}{space 3} .4627884
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{txt}{space 29}102  {c |}{col 35}{res}{space 2} .3127764{col 47}{space 2}  .210297{col 58}{space 1}    1.49{col 67}{space 3}0.140{col 75}{space 4}-.1042504{col 88}{space 3} .7298032
{txt}{space 29}103  {c |}{col 35}{res}{space 2} .0916522{col 47}{space 2} .1135694{col 58}{space 1}    0.81{col 67}{space 3}0.421{col 75}{space 4}-.1335601{col 88}{space 3} .3168645
{txt}{space 29}104  {c |}{col 35}{res}{space 2}-.1594188{col 47}{space 2} .0625763{col 58}{space 1}   -2.55{col 67}{space 3}0.012{col 75}{space 4}  -.28351{col 88}{space 3}-.0353276
{txt}{space 29}105  {c |}{col 35}{res}{space 2} .2524483{col 47}{space 2} .1981833{col 58}{space 1}    1.27{col 67}{space 3}0.206{col 75}{space 4}-.1405565{col 88}{space 3} .6454532
{txt}{space 33} {c |}
{space 29}year {c |}
{space 28}2011  {c |}{col 35}{res}{space 2}-.0010691{col 47}{space 2} .0036464{col 58}{space 1}   -0.29{col 67}{space 3}0.770{col 75}{space 4}   -.0083{col 88}{space 3} .0061617
{txt}{space 28}2012  {c |}{col 35}{res}{space 2} .0122991{col 47}{space 2} .0047321{col 58}{space 1}    2.60{col 67}{space 3}0.011{col 75}{space 4} .0029151{col 88}{space 3} .0216831
{txt}{space 28}2013  {c |}{col 35}{res}{space 2} .0148073{col 47}{space 2} .0059637{col 58}{space 1}    2.48{col 67}{space 3}0.015{col 75}{space 4} .0029811{col 88}{space 3} .0266334
{txt}{space 28}2014  {c |}{col 35}{res}{space 2} .0155716{col 47}{space 2} .0071533{col 58}{space 1}    2.18{col 67}{space 3}0.032{col 75}{space 4} .0013864{col 88}{space 3} .0297568
{txt}{space 28}2015  {c |}{col 35}{res}{space 2} .0099755{col 47}{space 2} .0089058{col 58}{space 1}    1.12{col 67}{space 3}0.265{col 75}{space 4}-.0076851{col 88}{space 3} .0276361
{txt}{space 28}2016  {c |}{col 35}{res}{space 2} .0088992{col 47}{space 2} .0085976{col 58}{space 1}    1.04{col 67}{space 3}0.303{col 75}{space 4}-.0081503{col 88}{space 3} .0259486
{txt}{space 28}2017  {c |}{col 35}{res}{space 2} .0138675{col 47}{space 2} .0132037{col 58}{space 1}    1.05{col 67}{space 3}0.296{col 75}{space 4}-.0123158{col 88}{space 3} .0400509
{txt}{space 28}2018  {c |}{col 35}{res}{space 2}-.0129918{col 47}{space 2}  .012172{col 58}{space 1}   -1.07{col 67}{space 3}0.288{col 75}{space 4}-.0371293{col 88}{space 3} .0111456
{txt}{space 28}2019  {c |}{col 35}{res}{space 2} -.044199{col 47}{space 2} .0132022{col 58}{space 1}   -3.35{col 67}{space 3}0.001{col 75}{space 4}-.0703795{col 88}{space 3}-.0180185
{txt}{space 33} {c |}
{space 28}_cons {c |}{col 35}{res}{space 2} .1519997{col 47}{space 2} .5142463{col 58}{space 1}    0.30{col 67}{space 3}0.768{col 75}{space 4}-.8677701{col 88}{space 3} 1.171769
{txt}{hline 34}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1984008{col 39} -1922377{col 50}    18{col 58}  3844791{col 69}  3845020
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. ** BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. lincom c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0540032{col 26}{space 2} .0351111{col 37}{space 1}    1.54{col 46}{space 3}0.127{col 54}{space 4}-.0156235{col 67}{space 3} .1236299
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0499643{col 26}{space 2} .0179561{col 37}{space 1}    2.78{col 46}{space 3}0.006{col 54}{space 4} .0143566{col 67}{space 3} .0855721
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. *
. *
. 
.   
. *** MODEL E3: CONDITIONAL RESPONSES BY MINORITY WOMEN VERSUS WHITE WOMEN [BASELINE CATEGORY: MEN RESPONDENTS] -- GENDER BETWEEN-IDENTITY GROUP STATUS DIFFERENTIAL MODEL: [WOMEN SUPERVISORS WITHIN AGENCY j IN YEAR t / MEN SUPERVISORS WITHIN AGENCY j IN YEAR t] / [WOMEN NON-SUPERVISORS WITHIN AGENCY j IN YEAR t / MEN NON-SUPERVISORS WITHIN AGENCY j IN YEAR t]  -- CONTROLLING FOR GENDER SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL ***
. 
. regress lnjustice2zeroadj   c.ln_ratio_fmsup_fmsub##i.women_het   ln_ratio_fem_tot_men_tot  minority  supervisor  topoffgender_2 lntotworkforce_count  ln_professionals_total_ratio   i.agencyid i.year, vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(19, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0483
                                                {txt}Root MSE          =    {res} .52085

{txt}{ralign 98:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 33}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 34}{c |}{col 46}    Robust
{col 1}               lnjustice2zeroadj{col 34}{c |} Coefficient{col 46}  std. err.{col 58}      t{col 66}   P>|t|{col 74}     [95% con{col 87}f. interval]
{hline 33}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}ln_ratio_fmsup_fmsub {c |}{col 34}{res}{space 2} .1308531{col 46}{space 2} .0474076{col 57}{space 1}    2.76{col 66}{space 3}0.007{col 74}{space 4} .0368421{col 87}{space 3} .2248641
{txt}{space 32} {c |}
{space 23}women_het {c |}
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{txt}{space 29}92  {c |}{col 34}{res}{space 2} .0803401{col 46}{space 2} .0488743{col 57}{space 1}    1.64{col 66}{space 3}0.103{col 74}{space 4}-.0165795{col 87}{space 3} .1772598
{txt}{space 29}93  {c |}{col 34}{res}{space 2} .4177341{col 46}{space 2} .1516544{col 57}{space 1}    2.75{col 66}{space 3}0.007{col 74}{space 4} .1169977{col 87}{space 3} .7184705
{txt}{space 29}94  {c |}{col 34}{res}{space 2} .4430113{col 46}{space 2} .1768688{col 57}{space 1}    2.50{col 66}{space 3}0.014{col 74}{space 4} .0922739{col 87}{space 3} .7937486
{txt}{space 29}95  {c |}{col 34}{res}{space 2}  .167141{col 46}{space 2} .1542045{col 57}{space 1}    1.08{col 66}{space 3}0.281{col 74}{space 4}-.1386522{col 87}{space 3} .4729343
{txt}{space 29}96  {c |}{col 34}{res}{space 2} .3548168{col 46}{space 2} .1595874{col 57}{space 1}    2.22{col 66}{space 3}0.028{col 74}{space 4} .0383491{col 87}{space 3} .6712845
{txt}{space 29}97  {c |}{col 34}{res}{space 2} .3959009{col 46}{space 2} .1544786{col 57}{space 1}    2.56{col 66}{space 3}0.012{col 74}{space 4}  .089564{col 87}{space 3} .7022378
{txt}{space 29}98  {c |}{col 34}{res}{space 2} .5534085{col 46}{space 2} .1904414{col 57}{space 1}    2.91{col 66}{space 3}0.004{col 74}{space 4} .1757561{col 87}{space 3} .9310609
{txt}{space 29}99  {c |}{col 34}{res}{space 2} .1215829{col 46}{space 2} .1044671{col 57}{space 1}    1.16{col 66}{space 3}0.247{col 74}{space 4}-.0855793{col 87}{space 3}  .328745
{txt}{space 28}100  {c |}{col 34}{res}{space 2} .2006463{col 46}{space 2} .1567822{col 57}{space 1}    1.28{col 66}{space 3}0.203{col 74}{space 4}-.1102587{col 87}{space 3} .5115513
{txt}{space 28}101  {c |}{col 34}{res}{space 2} .4151074{col 46}{space 2} .1399141{col 57}{space 1}    2.97{col 66}{space 3}0.004{col 74}{space 4} .1376525{col 87}{space 3} .6925622
{txt}{space 28}102  {c |}{col 34}{res}{space 2}  .274885{col 46}{space 2} .1647525{col 57}{space 1}    1.67{col 66}{space 3}0.098{col 74}{space 4}-.0518253{col 87}{space 3} .6015954
{txt}{space 28}103  {c |}{col 34}{res}{space 2} .0881812{col 46}{space 2} .1131113{col 57}{space 1}    0.78{col 66}{space 3}0.437{col 74}{space 4}-.1361228{col 87}{space 3} .3124853
{txt}{space 28}104  {c |}{col 34}{res}{space 2}-.0992626{col 46}{space 2} .0893084{col 57}{space 1}   -1.11{col 66}{space 3}0.269{col 74}{space 4}-.2763645{col 87}{space 3} .0778393
{txt}{space 28}105  {c |}{col 34}{res}{space 2} .3338974{col 46}{space 2} .1585694{col 57}{space 1}    2.11{col 66}{space 3}0.038{col 74}{space 4} .0194484{col 87}{space 3} .6483464
{txt}{space 32} {c |}
{space 28}year {c |}
{space 27}2011  {c |}{col 34}{res}{space 2}-.0031046{col 46}{space 2} .0033514{col 57}{space 1}   -0.93{col 66}{space 3}0.356{col 74}{space 4}-.0097505{col 87}{space 3} .0035413
{txt}{space 27}2012  {c |}{col 34}{res}{space 2} .0071687{col 46}{space 2} .0052884{col 57}{space 1}    1.36{col 66}{space 3}0.178{col 74}{space 4}-.0033184{col 87}{space 3} .0176557
{txt}{space 27}2013  {c |}{col 34}{res}{space 2} .0099109{col 46}{space 2} .0059525{col 57}{space 1}    1.66{col 66}{space 3}0.099{col 74}{space 4}-.0018932{col 87}{space 3}  .021715
{txt}{space 27}2014  {c |}{col 34}{res}{space 2} .0092246{col 46}{space 2} .0080919{col 57}{space 1}    1.14{col 66}{space 3}0.257{col 74}{space 4}-.0068219{col 87}{space 3} .0252712
{txt}{space 27}2015  {c |}{col 34}{res}{space 2} .0035967{col 46}{space 2} .0096587{col 57}{space 1}    0.37{col 66}{space 3}0.710{col 74}{space 4}-.0155569{col 87}{space 3} .0227502
{txt}{space 27}2016  {c |}{col 34}{res}{space 2} .0012651{col 46}{space 2} .0082552{col 57}{space 1}    0.15{col 66}{space 3}0.879{col 74}{space 4}-.0151053{col 87}{space 3} .0176354
{txt}{space 27}2017  {c |}{col 34}{res}{space 2} .0090646{col 46}{space 2} .0112206{col 57}{space 1}    0.81{col 66}{space 3}0.421{col 74}{space 4}-.0131863{col 87}{space 3} .0313155
{txt}{space 27}2018  {c |}{col 34}{res}{space 2}-.0211296{col 46}{space 2} .0088986{col 57}{space 1}   -2.37{col 66}{space 3}0.019{col 74}{space 4}-.0387759{col 87}{space 3}-.0034833
{txt}{space 27}2019  {c |}{col 34}{res}{space 2}-.0516385{col 46}{space 2} .0099086{col 57}{space 1}   -5.21{col 66}{space 3}0.000{col 74}{space 4}-.0712876{col 87}{space 3}-.0319895
{txt}{space 32} {c |}
{space 27}_cons {c |}{col 34}{res}{space 2} .0360658{col 46}{space 2} .4324624{col 57}{space 1}    0.08{col 66}{space 3}0.934{col 74}{space 4}-.8215233{col 87}{space 3} .8936549
{txt}{hline 33}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1984008{col 39} -1921998{col 50}    20{col 58}  3844037{col 69}  3844292
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. ** BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN GENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1308531{col 26}{space 2} .0474076{col 37}{space 1}    2.76{col 46}{space 3}0.007{col 54}{space 4} .0368421{col 67}{space 3} .2248641
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.women_het#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.women_het#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0037445{col 26}{space 2} .0218225{col 37}{space 1}    0.17{col 46}{space 3}0.864{col 54}{space 4}-.0395304{col 67}{space 3} .0470194
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.women_het#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.women_het#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0127411{col 26}{space 2} .0249305{col 37}{space 1}    0.51{col 46}{space 3}0.610{col 54}{space 4}-.0366971{col 67}{space 3} .0621793
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.women_het#c.ln_ratio_fmsup_fmsub -  1.women_het#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.women_het#c.ln_ratio_fmsup_fmsub + 2.women_het#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0089966{col 26}{space 2}  .017942{col 37}{space 1}    0.50{col 46}{space 3}0.617{col 54}{space 4} -.026583{col 67}{space 3} .0445762
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. 
. 
.    
. *** MODEL E4: CONDITIONAL RESPONSES BY MINORITY WOMEN VERSUS MINORITY MEN [BASELINE CATEGORY: NON-MINORITY RESPONDENTS] -- RACIAL/ETHNIC BETWEEN-IDENTITY GROUP STATUS DIFFERENTIAL MODEL: [MINORITY SUPERVISORS WITHIN AGENCY j IN YEAR t / NON-MINORITY SUPERVISORS WITHIN AGENCY j IN YEAR t] / [MINORITY NON-SUPERVISORS WITHIN AGENCY j IN YEAR t / NON-MINORITY NON-SUPERVISORS WITHIN AGENCY j IN YEAR t] -- CONTROLLING FOR RACIAL/ETHNIC SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL ***
. 
. regress  lnjustice2zeroadj   c.ln_ratio_mnmsup_mnmsub##i.minority_het   ln_ratio_min_tot_nmin_tot   gender supervisor  topoffminority_2 lntotworkforce_count  ln_professionals_total_ratio   i.agencyid i.year if e(sample), vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(19, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0482
                                                {txt}Root MSE          =    {res} .52086

{txt}{ralign 103:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 38}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 39}{c |}{col 51}    Robust
{col 1}                    lnjustice2zeroadj{col 39}{c |} Coefficient{col 51}  std. err.{col 63}      t{col 71}   P>|t|{col 79}     [95% con{col 92}f. interval]
{hline 38}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}ln_ratio_mnmsup_mnmsub {c |}{col 39}{res}{space 2} .0553047{col 51}{space 2} .0353774{col 62}{space 1}    1.56{col 71}{space 3}0.121{col 79}{space 4}  -.01485{col 92}{space 3} .1254594
{txt}{space 37} {c |}
{space 25}minority_het {c |}
{space 35}1  {c |}{col 39}{res}{space 2}-.0254514{col 51}{space 2}  .006705{col 62}{space 1}   -3.80{col 71}{space 3}0.000{col 79}{space 4}-.0387478{col 92}{space 3}-.0121551
{txt}{space 35}2  {c |}{col 39}{res}{space 2}-.0508053{col 51}{space 2} .0072992{col 62}{space 1}   -6.96{col 71}{space 3}0.000{col 79}{space 4}-.0652799{col 92}{space 3}-.0363308
{txt}{space 37} {c |}
minority_het#c.ln_ratio_mnmsup_mnmsub {c |}
{space 35}1  {c |}{col 39}{res}{space 2} .0289676{col 51}{space 2} .0158183{col 62}{space 1}    1.83{col 71}{space 3}0.070{col 79}{space 4}-.0024007{col 92}{space 3} .0603358
{txt}{space 35}2  {c |}{col 39}{res}{space 2} .0575381{col 51}{space 2} .0200962{col 62}{space 1}    2.86{col 71}{space 3}0.005{col 79}{space 4} .0176865{col 92}{space 3} .0973897
{txt}{space 37} {c |}
{space 12}ln_ratio_min_tot_nmin_tot {c |}{col 39}{res}{space 2} .0228231{col 51}{space 2} .0499976{col 62}{space 1}    0.46{col 71}{space 3}0.649{col 79}{space 4} -.076324{col 92}{space 3} .1219702
{txt}{space 31}gender {c |}{col 39}{res}{space 2}-.0178491{col 51}{space 2} .0053324{col 62}{space 1}   -3.35{col 71}{space 3}0.001{col 79}{space 4}-.0284234{col 92}{space 3}-.0072748
{txt}{space 27}supervisor {c |}{col 39}{res}{space 2} .1659067{col 51}{space 2} .0079465{col 62}{space 1}   20.88{col 71}{space 3}0.000{col 79}{space 4} .1501485{col 92}{space 3} .1816649
{txt}{space 21}topoffminority_2 {c |}{col 39}{res}{space 2} .0071672{col 51}{space 2} .0071773{col 62}{space 1}    1.00{col 71}{space 3}0.320{col 79}{space 4}-.0070657{col 92}{space 3} .0214001
{txt}{space 17}lntotworkforce_count {c |}{col 39}{res}{space 2} .0638889{col 51}{space 2} .0408974{col 62}{space 1}    1.56{col 71}{space 3}0.121{col 79}{space 4}-.0172121{col 92}{space 3}   .14499
{txt}{space 9}ln_professionals_total_ratio {c |}{col 39}{res}{space 2} .0251938{col 51}{space 2}  .049985{col 62}{space 1}    0.50{col 71}{space 3}0.615{col 79}{space 4}-.0739284{col 92}{space 3}  .124316
{txt}{space 37} {c |}
{space 29}agencyid {c |}
{space 35}2  {c |}{col 39}{res}{space 2} .1933313{col 51}{space 2} .1271702{col 62}{space 1}    1.52{col 71}{space 3}0.131{col 79}{space 4}-.0588519{col 92}{space 3} .4455145
{txt}{space 35}3  {c |}{col 39}{res}{space 2}-.0432426{col 51}{space 2}  .057144{col 62}{space 1}   -0.76{col 71}{space 3}0.451{col 79}{space 4}-.1565613{col 92}{space 3} .0700762
{txt}{space 35}4  {c |}{col 39}{res}{space 2} .2269896{col 51}{space 2} .1640844{col 62}{space 1}    1.38{col 71}{space 3}0.170{col 79}{space 4}-.0983958{col 92}{space 3}  .552375
{txt}{space 35}5  {c |}{col 39}{res}{space 2} .1619306{col 51}{space 2} .1276167{col 62}{space 1}    1.27{col 71}{space 3}0.207{col 79}{space 4}-.0911381{col 92}{space 3} .4149994
{txt}{space 35}6  {c |}{col 39}{res}{space 2} .1206813{col 51}{space 2} .1232213{col 62}{space 1}    0.98{col 71}{space 3}0.330{col 79}{space 4}-.1236711{col 92}{space 3} .3650338
{txt}{space 35}7  {c |}{col 39}{res}{space 2} .2335157{col 51}{space 2} .2161617{col 62}{space 1}    1.08{col 71}{space 3}0.283{col 79}{space 4}-.1951411{col 92}{space 3} .6621725
{txt}{space 35}8  {c |}{col 39}{res}{space 2} .2102326{col 51}{space 2} .1649705{col 62}{space 1}    1.27{col 71}{space 3}0.205{col 79}{space 4}  -.11691{col 92}{space 3} .5373752
{txt}{space 35}9  {c |}{col 39}{res}{space 2} -.050246{col 51}{space 2} .0239421{col 62}{space 1}   -2.10{col 71}{space 3}0.038{col 79}{space 4} -.097724{col 92}{space 3} -.002768
{txt}{space 34}10  {c |}{col 39}{res}{space 2}  .165474{col 51}{space 2} .2259073{col 62}{space 1}    0.73{col 71}{space 3}0.466{col 79}{space 4}-.2825086{col 92}{space 3} .6134566
{txt}{space 34}11  {c |}{col 39}{res}{space 2} .1410654{col 51}{space 2} .1038092{col 62}{space 1}    1.36{col 71}{space 3}0.177{col 79}{space 4}-.0647923{col 92}{space 3}  .346923
{txt}{space 34}12  {c |}{col 39}{res}{space 2}  .341489{col 51}{space 2} .2134238{col 62}{space 1}    1.60{col 71}{space 3}0.113{col 79}{space 4}-.0817384{col 92}{space 3} .7647165
{txt}{space 34}13  {c |}{col 39}{res}{space 2} .3319003{col 51}{space 2} .1701631{col 62}{space 1}    1.95{col 71}{space 3}0.054{col 79}{space 4}-.0055396{col 92}{space 3} .6693401
{txt}{space 34}14  {c |}{col 39}{res}{space 2} .1706246{col 51}{space 2} .1176283{col 62}{space 1}    1.45{col 71}{space 3}0.150{col 79}{space 4}-.0626368{col 92}{space 3}  .403886
{txt}{space 34}15  {c |}{col 39}{res}{space 2} .2993125{col 51}{space 2} .1570978{col 62}{space 1}    1.91{col 71}{space 3}0.060{col 79}{space 4}-.0122184{col 92}{space 3} .6108434
{txt}{space 34}16  {c |}{col 39}{res}{space 2}  .227575{col 51}{space 2} .2905763{col 62}{space 1}    0.78{col 71}{space 3}0.435{col 79}{space 4}-.3486486{col 92}{space 3} .8037987
{txt}{space 34}17  {c |}{col 39}{res}{space 2} .0494006{col 51}{space 2} .1823987{col 62}{space 1}    0.27{col 71}{space 3}0.787{col 79}{space 4} -.312303{col 92}{space 3} .4111042
{txt}{space 34}18  {c |}{col 39}{res}{space 2} .3031014{col 51}{space 2} .1740788{col 62}{space 1}    1.74{col 71}{space 3}0.085{col 79}{space 4}-.0421033{col 92}{space 3} .6483061
{txt}{space 34}19  {c |}{col 39}{res}{space 2}  .175647{col 51}{space 2} .1176847{col 62}{space 1}    1.49{col 71}{space 3}0.139{col 79}{space 4}-.0577262{col 92}{space 3} .4090202
{txt}{space 34}20  {c |}{col 39}{res}{space 2} .0197202{col 51}{space 2}  .124107{col 62}{space 1}    0.16{col 71}{space 3}0.874{col 79}{space 4}-.2263887{col 92}{space 3} .2658292
{txt}{space 34}21  {c |}{col 39}{res}{space 2} .1857661{col 51}{space 2} .1106642{col 62}{space 1}    1.68{col 71}{space 3}0.096{col 79}{space 4}-.0336852{col 92}{space 3} .4052173
{txt}{space 34}22  {c |}{col 39}{res}{space 2} .1757197{col 51}{space 2} .1749912{col 62}{space 1}    1.00{col 71}{space 3}0.318{col 79}{space 4}-.1712945{col 92}{space 3} .5227339
{txt}{space 34}23  {c |}{col 39}{res}{space 2}-.1112248{col 51}{space 2} .0872298{col 62}{space 1}   -1.28{col 71}{space 3}0.205{col 79}{space 4}-.2842048{col 92}{space 3} .0617551
{txt}{space 34}24  {c |}{col 39}{res}{space 2} .2595602{col 51}{space 2} .1235566{col 62}{space 1}    2.10{col 71}{space 3}0.038{col 79}{space 4} .0145428{col 92}{space 3} .5045777
{txt}{space 34}25  {c |}{col 39}{res}{space 2} .1799889{col 51}{space 2} .1439865{col 62}{space 1}    1.25{col 71}{space 3}0.214{col 79}{space 4}-.1055418{col 92}{space 3} .4655196
{txt}{space 34}26  {c |}{col 39}{res}{space 2} .0335479{col 51}{space 2} .1275191{col 62}{space 1}    0.26{col 71}{space 3}0.793{col 79}{space 4}-.2193272{col 92}{space 3} .2864231
{txt}{space 34}27  {c |}{col 39}{res}{space 2}  .272608{col 51}{space 2} .2007428{col 62}{space 1}    1.36{col 71}{space 3}0.177{col 79}{space 4}-.1254726{col 92}{space 3} .6706886
{txt}{space 34}28  {c |}{col 39}{res}{space 2}-.0716335{col 51}{space 2} .1088088{col 62}{space 1}   -0.66{col 71}{space 3}0.512{col 79}{space 4}-.2874054{col 92}{space 3} .1441384
{txt}{space 34}29  {c |}{col 39}{res}{space 2} .0702226{col 51}{space 2} .1838614{col 62}{space 1}    0.38{col 71}{space 3}0.703{col 79}{space 4}-.2943814{col 92}{space 3} .4348267
{txt}{space 34}30  {c |}{col 39}{res}{space 2} .1103851{col 51}{space 2} .1689252{col 62}{space 1}    0.65{col 71}{space 3}0.515{col 79}{space 4}-.2245999{col 92}{space 3} .4453701
{txt}{space 34}31  {c |}{col 39}{res}{space 2}-.0849194{col 51}{space 2} .1762467{col 62}{space 1}   -0.48{col 71}{space 3}0.631{col 79}{space 4}-.4344233{col 92}{space 3} .2645845
{txt}{space 34}32  {c |}{col 39}{res}{space 2} .2053758{col 51}{space 2} .1431488{col 62}{space 1}    1.43{col 71}{space 3}0.154{col 79}{space 4}-.0784936{col 92}{space 3} .4892452
{txt}{space 34}33  {c |}{col 39}{res}{space 2} .1182433{col 51}{space 2} .0890195{col 62}{space 1}    1.33{col 71}{space 3}0.187{col 79}{space 4}-.0582858{col 92}{space 3} .2947724
{txt}{space 34}34  {c |}{col 39}{res}{space 2}-.0681993{col 51}{space 2} .2325304{col 62}{space 1}   -0.29{col 71}{space 3}0.770{col 79}{space 4}-.5293158{col 92}{space 3} .3929173
{txt}{space 34}35  {c |}{col 39}{res}{space 2} .1035431{col 51}{space 2}  .108297{col 62}{space 1}    0.96{col 71}{space 3}0.341{col 79}{space 4}-.1112139{col 92}{space 3} .3183001
{txt}{space 34}36  {c |}{col 39}{res}{space 2} .1827798{col 51}{space 2}  .140661{col 62}{space 1}    1.30{col 71}{space 3}0.197{col 79}{space 4}-.0961562{col 92}{space 3} .4617159
{txt}{space 34}37  {c |}{col 39}{res}{space 2} .1701828{col 51}{space 2} .1229548{col 62}{space 1}    1.38{col 71}{space 3}0.169{col 79}{space 4}-.0736412{col 92}{space 3} .4140067
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{txt}{space 37} {c |}
{space 33}year {c |}
{space 32}2011  {c |}{col 39}{res}{space 2}-.0010775{col 51}{space 2} .0036511{col 62}{space 1}   -0.30{col 71}{space 3}0.768{col 79}{space 4}-.0083177{col 92}{space 3} .0061628
{txt}{space 32}2012  {c |}{col 39}{res}{space 2} .0121931{col 51}{space 2} .0047292{col 62}{space 1}    2.58{col 71}{space 3}0.011{col 79}{space 4}  .002815{col 92}{space 3} .0215712
{txt}{space 32}2013  {c |}{col 39}{res}{space 2} .0147574{col 51}{space 2} .0059693{col 62}{space 1}    2.47{col 71}{space 3}0.015{col 79}{space 4}   .00292{col 92}{space 3} .0265947
{txt}{space 32}2014  {c |}{col 39}{res}{space 2} .0155022{col 51}{space 2} .0071469{col 62}{space 1}    2.17{col 71}{space 3}0.032{col 79}{space 4} .0013295{col 92}{space 3} .0296748
{txt}{space 32}2015  {c |}{col 39}{res}{space 2} .0099264{col 51}{space 2} .0088898{col 62}{space 1}    1.12{col 71}{space 3}0.267{col 79}{space 4}-.0077024{col 92}{space 3} .0275553
{txt}{space 32}2016  {c |}{col 39}{res}{space 2} .0087664{col 51}{space 2} .0085863{col 62}{space 1}    1.02{col 71}{space 3}0.310{col 79}{space 4}-.0082607{col 92}{space 3} .0257934
{txt}{space 32}2017  {c |}{col 39}{res}{space 2} .0138299{col 51}{space 2} .0132191{col 62}{space 1}    1.05{col 71}{space 3}0.298{col 79}{space 4}-.0123842{col 92}{space 3} .0400439
{txt}{space 32}2018  {c |}{col 39}{res}{space 2}-.0130583{col 51}{space 2} .0121749{col 62}{space 1}   -1.07{col 71}{space 3}0.286{col 79}{space 4}-.0372017{col 92}{space 3} .0110851
{txt}{space 32}2019  {c |}{col 39}{res}{space 2}-.0442049{col 51}{space 2} .0131874{col 62}{space 1}   -3.35{col 71}{space 3}0.001{col 79}{space 4}-.0703561{col 92}{space 3}-.0180537
{txt}{space 37} {c |}
{space 32}_cons {c |}{col 39}{res}{space 2} .1510686{col 51}{space 2} .5147278{col 62}{space 1}    0.29{col 71}{space 3}0.770{col 79}{space 4} -.869656{col 92}{space 3} 1.171793
{txt}{hline 38}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1984008{col 39} -1922053{col 50}    20{col 58}  3844145{col 69}  3844400
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. ** BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. lincom c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0553047{col 26}{space 2} .0353774{col 37}{space 1}    1.56{col 46}{space 3}0.121{col 54}{space 4}  -.01485{col 67}{space 3} .1254594
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority_het#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority_het#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0289676{col 26}{space 2} .0158183{col 37}{space 1}    1.83{col 46}{space 3}0.070{col 54}{space 4}-.0024007{col 67}{space 3} .0603358
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.minority_het#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.minority_het#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0575381{col 26}{space 2} .0200962{col 37}{space 1}    2.86{col 46}{space 3}0.005{col 54}{space 4} .0176865{col 67}{space 3} .0973897
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.minority_het#c.ln_ratio_mnmsup_mnmsub -  1.minority_het#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.minority_het#c.ln_ratio_mnmsup_mnmsub + 2.minority_het#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0285705{col 26}{space 2} .0145237{col 37}{space 1}    1.97{col 46}{space 3}0.052{col 54}{space 4}-.0002305{col 67}{space 3} .0573715
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. 
. 
. **********************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
. 
. 
. 
.    
. *** 4. CONDITIONAL-RESPONDENT MODELS EVALUATING THE RELATIONSHIP INVOLVING WITHIN-IDENTITY "OUT-GROUP" STATUS & BETWEEN-IDENTITY GROUP STATUS DIFFERENTIALS AS A MEANS TO FOSTER DIVERSITY AND INCLUSION IN THE U.S. CIVILIAN WORKFORCE  [BY NON-SUPERVISORS POSITIONS VERSUS SUPERVISORY POSITION] ***   
. 
. 
.    
. *** MODEL E5: CONDITIONAL RESPONSES BY GENDER & POSITION --  GENDER WITHIN-IDENTITY 'OUT-GROUP' STATUS DIFFERENTIAL MODEL: [WOMEN SUPERVISORS WITHIN AGENCY j IN YEAR t / WOMEN NON-SUPERVISORS WITHIN AGENCY j IN YEAR t] -- CONTROLLING FOR GENDER SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL ***
. 
. regress  lnjustice2zeroadj   c.ln_ratio_fmsup_fmsub##i.gender##i.supervisor   ln_ratio_fem_tot_men_tot   minority  topoffgender_2 lntotworkforce_count  ln_professionals_total_ratio   i.agencyid i.year, vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(20, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0480
                                                {txt}Root MSE          =    {res} .52091

{txt}{ralign 106:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 41}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 42}{c |}{col 54}    Robust
{col 1}                       lnjustice2zeroadj{col 42}{c |} Coefficient{col 54}  std. err.{col 66}      t{col 74}   P>|t|{col 82}     [95% con{col 95}f. interval]
{hline 41}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 20}ln_ratio_fmsup_fmsub {c |}{col 42}{res}{space 2} .1249375{col 54}{space 2} .0499871{col 65}{space 1}    2.50{col 74}{space 3}0.014{col 82}{space 4} .0258113{col 95}{space 3} .2240638
{txt}{space 32}1.gender {c |}{col 42}{res}{space 2}-.0292504{col 54}{space 2}  .010588{col 65}{space 1}   -2.76{col 74}{space 3}0.007{col 82}{space 4}-.0502469{col 95}{space 3} -.008254
{txt}{space 40} {c |}
{space 11}gender#c.ln_ratio_fmsup_fmsub {c |}
{space 38}1  {c |}{col 42}{res}{space 2} .0048677{col 54}{space 2} .0273305{col 65}{space 1}    0.18{col 74}{space 3}0.859{col 82}{space 4}-.0493297{col 95}{space 3} .0590652
{txt}{space 40} {c |}
{space 28}1.supervisor {c |}{col 42}{res}{space 2} .1734946{col 54}{space 2} .0183574{col 65}{space 1}    9.45{col 74}{space 3}0.000{col 82}{space 4} .1370912{col 95}{space 3}  .209898
{txt}{space 40} {c |}
{space 7}supervisor#c.ln_ratio_fmsup_fmsub {c |}
{space 38}1  {c |}{col 42}{res}{space 2} .0252514{col 54}{space 2} .0368931{col 65}{space 1}    0.68{col 74}{space 3}0.495{col 82}{space 4}-.0479091{col 95}{space 3} .0984119
{txt}{space 40} {c |}
{space 23}gender#supervisor {c |}
{space 36}1 1  {c |}{col 42}{res}{space 2} .0077875{col 54}{space 2} .0153693{col 65}{space 1}    0.51{col 74}{space 3}0.613{col 82}{space 4}-.0226904{col 95}{space 3} .0382654
{txt}{space 40} {c |}
gender#supervisor#c.ln_ratio_fmsup_fmsub {c |}
{space 36}1 1  {c |}{col 42}{res}{space 2} .0129625{col 54}{space 2} .0296579{col 65}{space 1}    0.44{col 74}{space 3}0.663{col 82}{space 4}-.0458502{col 95}{space 3} .0717752
{txt}{space 40} {c |}
{space 16}ln_ratio_fem_tot_men_tot {c |}{col 42}{res}{space 2}-.0264895{col 54}{space 2} .0651876{col 65}{space 1}   -0.41{col 74}{space 3}0.685{col 82}{space 4}-.1557589{col 95}{space 3} .1027799
{txt}{space 32}minority {c |}{col 42}{res}{space 2}-.0524229{col 54}{space 2} .0037389{col 65}{space 1}  -14.02{col 74}{space 3}0.000{col 82}{space 4}-.0598373{col 95}{space 3}-.0450084
{txt}{space 26}topoffgender_2 {c |}{col 42}{res}{space 2}-.0049736{col 54}{space 2} .0051615{col 65}{space 1}   -0.96{col 74}{space 3}0.337{col 82}{space 4} -.015209{col 95}{space 3} .0052617
{txt}{space 20}lntotworkforce_count {c |}{col 42}{res}{space 2} .0720139{col 54}{space 2} .0338369{col 65}{space 1}    2.13{col 74}{space 3}0.036{col 82}{space 4}  .004914{col 95}{space 3} .1391138
{txt}{space 12}ln_professionals_total_ratio {c |}{col 42}{res}{space 2} .0168329{col 54}{space 2} .0440791{col 65}{space 1}    0.38{col 74}{space 3}0.703{col 82}{space 4}-.0705776{col 95}{space 3} .1042434
{txt}{space 40} {c |}
{space 32}agencyid {c |}
{space 38}2  {c |}{col 42}{res}{space 2} .2921257{col 54}{space 2} .1168491{col 65}{space 1}    2.50{col 74}{space 3}0.014{col 82}{space 4} .0604095{col 95}{space 3} .5238418
{txt}{space 38}3  {c |}{col 42}{res}{space 2} .0305239{col 54}{space 2} .0551132{col 65}{space 1}    0.55{col 74}{space 3}0.581{col 82}{space 4}-.0787677{col 95}{space 3} .1398154
{txt}{space 38}4  {c |}{col 42}{res}{space 2} .3963995{col 54}{space 2} .1562612{col 65}{space 1}    2.54{col 74}{space 3}0.013{col 82}{space 4} .0865276{col 95}{space 3} .7062714
{txt}{space 38}5  {c |}{col 42}{res}{space 2} .2451943{col 54}{space 2} .1074112{col 65}{space 1}    2.28{col 74}{space 3}0.024{col 82}{space 4}  .032194{col 95}{space 3} .4581947
{txt}{space 38}6  {c |}{col 42}{res}{space 2} .2032253{col 54}{space 2} .1140535{col 65}{space 1}    1.78{col 74}{space 3}0.078{col 82}{space 4}-.0229472{col 95}{space 3} .4293977
{txt}{space 38}7  {c |}{col 42}{res}{space 2}  .327377{col 54}{space 2} .1886081{col 65}{space 1}    1.74{col 74}{space 3}0.086{col 82}{space 4}  -.04664{col 95}{space 3}  .701394
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{txt}{space 37}82  {c |}{col 42}{res}{space 2} .3417359{col 54}{space 2} .1896248{col 65}{space 1}    1.80{col 74}{space 3}0.074{col 82}{space 4}-.0342971{col 95}{space 3}  .717769
{txt}{space 37}83  {c |}{col 42}{res}{space 2} .4036348{col 54}{space 2} .1496697{col 65}{space 1}    2.70{col 74}{space 3}0.008{col 82}{space 4} .1068341{col 95}{space 3} .7004354
{txt}{space 37}84  {c |}{col 42}{res}{space 2}  .360908{col 54}{space 2} .1906566{col 65}{space 1}    1.89{col 74}{space 3}0.061{col 82}{space 4}-.0171712{col 95}{space 3} .7389872
{txt}{space 37}85  {c |}{col 42}{res}{space 2} .4378694{col 54}{space 2} .1543649{col 65}{space 1}    2.84{col 74}{space 3}0.005{col 82}{space 4}  .131758{col 95}{space 3} .7439808
{txt}{space 37}86  {c |}{col 42}{res}{space 2} .4351878{col 54}{space 2} .1948765{col 65}{space 1}    2.23{col 74}{space 3}0.028{col 82}{space 4} .0487403{col 95}{space 3} .8216352
{txt}{space 37}87  {c |}{col 42}{res}{space 2} .4903616{col 54}{space 2} .1974378{col 65}{space 1}    2.48{col 74}{space 3}0.015{col 82}{space 4} .0988351{col 95}{space 3} .8818881
{txt}{space 37}88  {c |}{col 42}{res}{space 2} .2414364{col 54}{space 2} .1401585{col 65}{space 1}    1.72{col 74}{space 3}0.088{col 82}{space 4}-.0365032{col 95}{space 3}  .519376
{txt}{space 37}89  {c |}{col 42}{res}{space 2}  .278183{col 54}{space 2} .1498483{col 65}{space 1}    1.86{col 74}{space 3}0.066{col 82}{space 4}-.0189718{col 95}{space 3} .5753378
{txt}{space 37}90  {c |}{col 42}{res}{space 2} .0989837{col 54}{space 2}  .122359{col 65}{space 1}    0.81{col 74}{space 3}0.420{col 82}{space 4}-.1436587{col 95}{space 3} .3416261
{txt}{space 37}91  {c |}{col 42}{res}{space 2} .1924608{col 54}{space 2} .1137464{col 65}{space 1}    1.69{col 74}{space 3}0.094{col 82}{space 4}-.0331025{col 95}{space 3} .4180241
{txt}{space 37}92  {c |}{col 42}{res}{space 2} .0811819{col 54}{space 2} .0486677{col 65}{space 1}    1.67{col 74}{space 3}0.098{col 82}{space 4} -.015328{col 95}{space 3} .1776919
{txt}{space 37}93  {c |}{col 42}{res}{space 2} .4216419{col 54}{space 2} .1509542{col 65}{space 1}    2.79{col 74}{space 3}0.006{col 82}{space 4} .1222941{col 95}{space 3} .7209897
{txt}{space 37}94  {c |}{col 42}{res}{space 2} .4454066{col 54}{space 2} .1756866{col 65}{space 1}    2.54{col 74}{space 3}0.013{col 82}{space 4} .0970135{col 95}{space 3} .7937998
{txt}{space 37}95  {c |}{col 42}{res}{space 2} .1714796{col 54}{space 2} .1533793{col 65}{space 1}    1.12{col 74}{space 3}0.266{col 82}{space 4}-.1326773{col 95}{space 3} .4756365
{txt}{space 37}96  {c |}{col 42}{res}{space 2} .3590179{col 54}{space 2} .1586021{col 65}{space 1}    2.26{col 74}{space 3}0.026{col 82}{space 4}  .044504{col 95}{space 3} .6735317
{txt}{space 37}97  {c |}{col 42}{res}{space 2} .4012644{col 54}{space 2} .1535453{col 65}{space 1}    2.61{col 74}{space 3}0.010{col 82}{space 4} .0967784{col 95}{space 3} .7057504
{txt}{space 37}98  {c |}{col 42}{res}{space 2} .5577637{col 54}{space 2} .1893352{col 65}{space 1}    2.95{col 74}{space 3}0.004{col 82}{space 4} .1823049{col 95}{space 3} .9332224
{txt}{space 37}99  {c |}{col 42}{res}{space 2} .1232556{col 54}{space 2}  .104068{col 65}{space 1}    1.18{col 74}{space 3}0.239{col 82}{space 4} -.083115{col 95}{space 3} .3296263
{txt}{space 36}100  {c |}{col 42}{res}{space 2} .2047319{col 54}{space 2} .1557734{col 65}{space 1}    1.31{col 74}{space 3}0.192{col 82}{space 4}-.1041726{col 95}{space 3} .5136364
{txt}{space 36}101  {c |}{col 42}{res}{space 2}  .418922{col 54}{space 2} .1388963{col 65}{space 1}    3.02{col 74}{space 3}0.003{col 82}{space 4} .1434855{col 95}{space 3} .6943585
{txt}{space 36}102  {c |}{col 42}{res}{space 2}  .276817{col 54}{space 2} .1643784{col 65}{space 1}    1.68{col 74}{space 3}0.095{col 82}{space 4}-.0491515{col 95}{space 3} .6027855
{txt}{space 36}103  {c |}{col 42}{res}{space 2} .0914419{col 54}{space 2} .1123238{col 65}{space 1}    0.81{col 74}{space 3}0.417{col 82}{space 4}-.1313003{col 95}{space 3} .3141842
{txt}{space 36}104  {c |}{col 42}{res}{space 2}-.0974879{col 54}{space 2} .0892585{col 65}{space 1}   -1.09{col 74}{space 3}0.277{col 82}{space 4}-.2744909{col 95}{space 3} .0795151
{txt}{space 36}105  {c |}{col 42}{res}{space 2} .3371846{col 54}{space 2} .1575595{col 65}{space 1}    2.14{col 74}{space 3}0.035{col 82}{space 4} .0247382{col 95}{space 3}  .649631
{txt}{space 40} {c |}
{space 36}year {c |}
{space 35}2011  {c |}{col 42}{res}{space 2} -.003074{col 54}{space 2}  .003355{col 65}{space 1}   -0.92{col 74}{space 3}0.362{col 82}{space 4}-.0097272{col 95}{space 3} .0035791
{txt}{space 35}2012  {c |}{col 42}{res}{space 2} .0071462{col 54}{space 2} .0053459{col 65}{space 1}    1.34{col 74}{space 3}0.184{col 82}{space 4} -.003455{col 95}{space 3} .0177473
{txt}{space 35}2013  {c |}{col 42}{res}{space 2} .0098433{col 54}{space 2} .0059818{col 65}{space 1}    1.65{col 74}{space 3}0.103{col 82}{space 4}-.0020188{col 95}{space 3} .0217054
{txt}{space 35}2014  {c |}{col 42}{res}{space 2} .0091755{col 54}{space 2}  .008155{col 65}{space 1}    1.13{col 74}{space 3}0.263{col 82}{space 4}-.0069961{col 95}{space 3} .0253471
{txt}{space 35}2015  {c |}{col 42}{res}{space 2} .0035662{col 54}{space 2} .0096862{col 65}{space 1}    0.37{col 74}{space 3}0.713{col 82}{space 4}-.0156419{col 95}{space 3} .0227742
{txt}{space 35}2016  {c |}{col 42}{res}{space 2} .0012653{col 54}{space 2} .0082828{col 65}{space 1}    0.15{col 74}{space 3}0.879{col 82}{space 4}-.0151598{col 95}{space 3} .0176904
{txt}{space 35}2017  {c |}{col 42}{res}{space 2} .0090449{col 54}{space 2} .0111917{col 65}{space 1}    0.81{col 74}{space 3}0.421{col 82}{space 4}-.0131488{col 95}{space 3} .0312385
{txt}{space 35}2018  {c |}{col 42}{res}{space 2}-.0211411{col 54}{space 2} .0089023{col 65}{space 1}   -2.37{col 74}{space 3}0.019{col 82}{space 4}-.0387947{col 95}{space 3}-.0034876
{txt}{space 35}2019  {c |}{col 42}{res}{space 2}-.0516897{col 54}{space 2} .0098819{col 65}{space 1}   -5.23{col 74}{space 3}0.000{col 82}{space 4} -.071286{col 95}{space 3}-.0320935
{txt}{space 40} {c |}
{space 35}_cons {c |}{col 42}{res}{space 2} .0282212{col 54}{space 2} .4297298{col 65}{space 1}    0.07{col 74}{space 3}0.948{col 82}{space 4}-.8239491{col 95}{space 3} .8803916
{txt}{hline 41}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1984008{col 39} -1922300{col 50}    21{col 58}  3844643{col 69}  3844910
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. ** BY NON-SUPERVISORS RESPONDENT: WITHIN-IDENTITY "OUT" GROUP STATUS DIFFERENTIAL BETWEEN GENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fmsup_fmsub 

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1249375{col 26}{space 2} .0499871{col 37}{space 1}    2.50{col 46}{space 3}0.014{col 54}{space 4} .0258113{col 67}{space 3} .2240638
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.gender#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.gender#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0048677{col 26}{space 2} .0273305{col 37}{space 1}    0.18{col 46}{space 3}0.859{col 54}{space 4}-.0493297{col 67}{space 3} .0590652
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *
. *
. *
. *
. 
. ** BY SUPERVISOR RESPONDENT: WITHIN-IDENTITY "OUT" GROUP STATUS DIFFERENTIAL BETWEEN GENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fmsup_fmsub + 1.supervisor#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fmsup_fmsub + 1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1501889{col 26}{space 2} .0505755{col 37}{space 1}    2.97{col 46}{space 3}0.004{col 54}{space 4} .0498958{col 67}{space 3} .2504821
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.gender#c.ln_ratio_fmsup_fmsub +  1.gender#1.supervisor#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.gender#c.ln_ratio_fmsup_fmsub + 1.gender#1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0178302{col 26}{space 2} .0214372{col 37}{space 1}    0.83{col 46}{space 3}0.407{col 54}{space 4}-.0246805{col 67}{space 3}  .060341
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. 
. 
. 
. *** MODEL E6: CONDITIONAL RESPONSES BY RACE/ETHNICITIY & POSITION -- RACIAL/ETHNIC WITHIN-'OUT-GROUP' STATUS DIFFERENTIAL MODEL: [MINORITY SUPERVISORS WITHIN AGENCY j IN YEAR t / NON-MINORITY NON-SUPERVISORS WITHIN AGENCY j IN YEAR t]  -- CONTROLLING FOR RACIAL/ETHNIC SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL ***
. 
. regress lnjustice2zeroadj   c.ln_ratio_mnmsup_mnmsub##i.minority##i.supervisor  ln_ratio_min_tot_nmin_tot   gender  topoffminority_2 lntotworkforce_count  ln_professionals_total_ratio   i.agencyid i.year, vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(20, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0480
                                                {txt}Root MSE          =    {res} .52092

{txt}{ralign 110:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 45}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 46}{c |}{col 58}    Robust
{col 1}                           lnjustice2zeroadj{col 46}{c |} Coefficient{col 58}  std. err.{col 70}      t{col 78}   P>|t|{col 86}     [95% con{col 99}f. interval]
{hline 45}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 22}ln_ratio_mnmsup_mnmsub {c |}{col 46}{res}{space 2} .0590666{col 58}{space 2} .0356709{col 69}{space 1}    1.66{col 78}{space 3}0.101{col 86}{space 4}-.0116702{col 99}{space 3} .1298034
{txt}{space 34}1.minority {c |}{col 46}{res}{space 2}-.0345643{col 58}{space 2} .0085825{col 69}{space 1}   -4.03{col 78}{space 3}0.000{col 86}{space 4}-.0515836{col 99}{space 3}-.0175449
{txt}{space 44} {c |}
{space 11}minority#c.ln_ratio_mnmsup_mnmsub {c |}
{space 42}1  {c |}{col 46}{res}{space 2} .0438845{col 58}{space 2} .0215859{col 69}{space 1}    2.03{col 78}{space 3}0.045{col 86}{space 4} .0010789{col 99}{space 3} .0866901
{txt}{space 44} {c |}
{space 32}1.supervisor {c |}{col 46}{res}{space 2} .1631193{col 58}{space 2}  .014214{col 69}{space 1}   11.48{col 78}{space 3}0.000{col 86}{space 4} .1349325{col 99}{space 3} .1913061
{txt}{space 44} {c |}
{space 9}supervisor#c.ln_ratio_mnmsup_mnmsub {c |}
{space 42}1  {c |}{col 46}{res}{space 2}-.0181021{col 58}{space 2} .0287922{col 69}{space 1}   -0.63{col 78}{space 3}0.531{col 86}{space 4}-.0751982{col 99}{space 3} .0389939
{txt}{space 44} {c |}
{space 25}minority#supervisor {c |}
{space 40}1 1  {c |}{col 46}{res}{space 2}-.0035808{col 58}{space 2} .0092111{col 69}{space 1}   -0.39{col 78}{space 3}0.698{col 86}{space 4}-.0218468{col 99}{space 3} .0146852
{txt}{space 44} {c |}
minority#supervisor#c.ln_ratio_mnmsup_mnmsub {c |}
{space 40}1 1  {c |}{col 46}{res}{space 2} .0254994{col 58}{space 2} .0191463{col 69}{space 1}    1.33{col 78}{space 3}0.186{col 86}{space 4}-.0124684{col 99}{space 3} .0634673
{txt}{space 44} {c |}
{space 19}ln_ratio_min_tot_nmin_tot {c |}{col 46}{res}{space 2} .0228286{col 58}{space 2} .0500993{col 69}{space 1}    0.46{col 78}{space 3}0.650{col 86}{space 4}-.0765201{col 99}{space 3} .1221774
{txt}{space 38}gender {c |}{col 46}{res}{space 2}-.0300958{col 58}{space 2} .0045583{col 69}{space 1}   -6.60{col 78}{space 3}0.000{col 86}{space 4}-.0391351{col 99}{space 3}-.0210566
{txt}{space 28}topoffminority_2 {c |}{col 46}{res}{space 2} .0072227{col 58}{space 2} .0071436{col 69}{space 1}    1.01{col 78}{space 3}0.314{col 86}{space 4}-.0069433{col 99}{space 3} .0213886
{txt}{space 24}lntotworkforce_count {c |}{col 46}{res}{space 2} .0643624{col 58}{space 2} .0408744{col 69}{space 1}    1.57{col 78}{space 3}0.118{col 86}{space 4} -.016693{col 99}{space 3} .1454179
{txt}{space 16}ln_professionals_total_ratio {c |}{col 46}{res}{space 2} .0250921{col 58}{space 2} .0498728{col 69}{space 1}    0.50{col 78}{space 3}0.616{col 86}{space 4}-.0738075{col 99}{space 3} .1239917
{txt}{space 44} {c |}
{space 36}agencyid {c |}
{space 42}2  {c |}{col 46}{res}{space 2} .1954052{col 58}{space 2} .1270197{col 69}{space 1}    1.54{col 78}{space 3}0.127{col 86}{space 4}-.0564797{col 99}{space 3} .4472901
{txt}{space 42}3  {c |}{col 46}{res}{space 2}-.0409369{col 58}{space 2} .0570484{col 69}{space 1}   -0.72{col 78}{space 3}0.475{col 86}{space 4}-.1540659{col 99}{space 3} .0721921
{txt}{space 42}4  {c |}{col 46}{res}{space 2} .2293672{col 58}{space 2} .1639192{col 69}{space 1}    1.40{col 78}{space 3}0.165{col 86}{space 4}-.0956907{col 99}{space 3} .5544251
{txt}{space 42}5  {c |}{col 46}{res}{space 2} .1634867{col 58}{space 2} .1276196{col 69}{space 1}    1.28{col 78}{space 3}0.203{col 86}{space 4}-.0895878{col 99}{space 3} .4165611
{txt}{space 42}6  {c |}{col 46}{res}{space 2} .1223723{col 58}{space 2} .1227839{col 69}{space 1}    1.00{col 78}{space 3}0.321{col 86}{space 4}-.1211127{col 99}{space 3} .3658574
{txt}{space 42}7  {c |}{col 46}{res}{space 2} .2344413{col 58}{space 2} .2162715{col 69}{space 1}    1.08{col 78}{space 3}0.281{col 86}{space 4}-.1944332{col 99}{space 3} .6633159
{txt}{space 42}8  {c |}{col 46}{res}{space 2} .2112443{col 58}{space 2} .1647084{col 69}{space 1}    1.28{col 78}{space 3}0.203{col 86}{space 4}-.1153786{col 99}{space 3} .5378672
{txt}{space 42}9  {c |}{col 46}{res}{space 2}-.0500991{col 58}{space 2} .0239522{col 69}{space 1}   -2.09{col 78}{space 3}0.039{col 86}{space 4}-.0975972{col 99}{space 3} -.002601
{txt}{space 41}10  {c |}{col 46}{res}{space 2} .1690332{col 58}{space 2} .2259959{col 69}{space 1}    0.75{col 78}{space 3}0.456{col 86}{space 4}-.2791251{col 99}{space 3} .6171916
{txt}{space 41}11  {c |}{col 46}{res}{space 2} .1433335{col 58}{space 2} .1040262{col 69}{space 1}    1.38{col 78}{space 3}0.171{col 86}{space 4}-.0629543{col 99}{space 3} .3496214
{txt}{space 41}12  {c |}{col 46}{res}{space 2} .3423862{col 58}{space 2} .2131817{col 69}{space 1}    1.61{col 78}{space 3}0.111{col 86}{space 4} -.080361{col 99}{space 3} .7651334
{txt}{space 41}13  {c |}{col 46}{res}{space 2} .3335714{col 58}{space 2} .1699372{col 69}{space 1}    1.96{col 78}{space 3}0.052{col 86}{space 4}-.0034205{col 99}{space 3} .6705633
{txt}{space 41}14  {c |}{col 46}{res}{space 2} .1718546{col 58}{space 2} .1173912{col 69}{space 1}    1.46{col 78}{space 3}0.146{col 86}{space 4}-.0609366{col 99}{space 3} .4046458
{txt}{space 41}15  {c |}{col 46}{res}{space 2}  .301905{col 58}{space 2} .1571184{col 69}{space 1}    1.92{col 78}{space 3}0.057{col 86}{space 4}-.0096667{col 99}{space 3} .6134767
{txt}{space 41}16  {c |}{col 46}{res}{space 2} .2266716{col 58}{space 2} .2908762{col 69}{space 1}    0.78{col 78}{space 3}0.438{col 86}{space 4}-.3501468{col 99}{space 3} .8034901
{txt}{space 41}17  {c |}{col 46}{res}{space 2} .0510674{col 58}{space 2} .1823014{col 69}{space 1}    0.28{col 78}{space 3}0.780{col 86}{space 4}-.3104431{col 99}{space 3} .4125778
{txt}{space 41}18  {c |}{col 46}{res}{space 2} .3051685{col 58}{space 2} .1738644{col 69}{space 1}    1.76{col 78}{space 3}0.082{col 86}{space 4}-.0396111{col 99}{space 3} .6499481
{txt}{space 41}19  {c |}{col 46}{res}{space 2} .1768394{col 58}{space 2} .1175864{col 69}{space 1}    1.50{col 78}{space 3}0.136{col 86}{space 4}-.0563389{col 99}{space 3} .4100177
{txt}{space 41}20  {c |}{col 46}{res}{space 2} .0216799{col 58}{space 2} .1240966{col 69}{space 1}    0.17{col 78}{space 3}0.862{col 86}{space 4}-.2244082{col 99}{space 3} .2677681
{txt}{space 41}21  {c |}{col 46}{res}{space 2} .1879886{col 58}{space 2} .1105609{col 69}{space 1}    1.70{col 78}{space 3}0.092{col 86}{space 4}-.0312579{col 99}{space 3} .4072351
{txt}{space 41}22  {c |}{col 46}{res}{space 2} .1775784{col 58}{space 2} .1749818{col 69}{space 1}    1.01{col 78}{space 3}0.313{col 86}{space 4}-.1694171{col 99}{space 3}  .524574
{txt}{space 41}23  {c |}{col 46}{res}{space 2}-.1097659{col 58}{space 2} .0872842{col 69}{space 1}   -1.26{col 78}{space 3}0.211{col 86}{space 4}-.2828537{col 99}{space 3} .0633219
{txt}{space 41}24  {c |}{col 46}{res}{space 2} .2605992{col 58}{space 2} .1235212{col 69}{space 1}    2.11{col 78}{space 3}0.037{col 86}{space 4} .0156521{col 99}{space 3} .5055463
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{txt}{hline 45}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1984008{col 39} -1922342{col 50}    21{col 58}  3844726{col 69}  3844993
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. 
. ** BY NON-SUPERVISORS RESPONDENT: WITHIN-IDENTITY "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. lincom c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0590666{col 26}{space 2} .0356709{col 37}{space 1}    1.66{col 46}{space 3}0.101{col 54}{space 4}-.0116702{col 67}{space 3} .1298034
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0438845{col 26}{space 2} .0215859{col 37}{space 1}    2.03{col 46}{space 3}0.045{col 54}{space 4} .0010789{col 67}{space 3} .0866901
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *
. *
. *
. *
. 
. ** BY SUPERVISOR RESPONDENT: WITHIN-IDENTITY "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. lincom c.ln_ratio_mnmsup_mnmsub + 1.supervisor#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_mnmsup_mnmsub + 1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0409644{col 26}{space 2} .0413208{col 37}{space 1}    0.99{col 46}{space 3}0.324{col 54}{space 4}-.0409762{col 67}{space 3} .1229051
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority#c.ln_ratio_mnmsup_mnmsub +  1.minority#1.supervisor#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority#c.ln_ratio_mnmsup_mnmsub + 1.minority#1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0693839{col 26}{space 2} .0145321{col 37}{space 1}    4.77{col 46}{space 3}0.000{col 54}{space 4} .0405662{col 67}{space 3} .0982016
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. * SUPERVISOR - NON-SUPERVISORY DIFFERENCE AMONG MINORITY RESPONDENT DIFFERENCES 
.  
. lincom  1.minority#c.ln_ratio_mnmsup_mnmsub +  1.minority#1.supervisor#c.ln_ratio_mnmsup_mnmsub - (1.minority#c.ln_ratio_mnmsup_mnmsub)

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority#1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0254994{col 26}{space 2} .0191463{col 37}{space 1}    1.33{col 46}{space 3}0.186{col 54}{space 4}-.0124684{col 67}{space 3} .0634673
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. ******************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
.    
. *** MODEL E7: CONDITIONAL RESPONSES BY GENDER & POSITION -- GENDER BETWEEN-IDENTITY GROUP STATUS DIFFERENTIAL MODEL: [WOMEN SUPERVISORS WITHIN AGENCY j IN YEAR t / MEN SUPERVISORS WITHIN AGENCY j IN YEAR t] / [WOMEN NON-SUPERVISORS WITHIN AGENCY j IN YEAR t / MEN NON-SUPERVISORS WITHIN AGENCY j IN YEAR t] -- CONTROLLING FOR GENDER SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL ***
. 
. regress lnjustice2zeroadj   c.ln_ratio_fmsup_fmsub##i.women_het##i.supervisor   ln_ratio_fem_tot_men_tot   minority   topoffgender_2 lntotworkforce_count  ln_professionals_total_ratio   i.agencyid i.year, vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(24, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0483
                                                {txt}Root MSE          =    {res} .52084

{txt}{ralign 109:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 44}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 45}{c |}{col 57}    Robust
{col 1}                          lnjustice2zeroadj{col 45}{c |} Coefficient{col 57}  std. err.{col 69}      t{col 77}   P>|t|{col 85}     [95% con{col 98}f. interval]
{hline 44}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}ln_ratio_fmsup_fmsub {c |}{col 45}{res}{space 2} .1237888{col 57}{space 2} .0501231{col 68}{space 1}    2.47{col 77}{space 3}0.015{col 85}{space 4} .0243928{col 98}{space 3} .2231847
{txt}{space 43} {c |}
{space 34}women_het {c |}
{space 41}1  {c |}{col 45}{res}{space 2}-.0180012{col 57}{space 2} .0108312{col 68}{space 1}   -1.66{col 77}{space 3}0.100{col 85}{space 4}-.0394798{col 98}{space 3} .0034775
{txt}{space 41}2  {c |}{col 45}{res}{space 2}-.0471977{col 57}{space 2} .0120506{col 68}{space 1}   -3.92{col 77}{space 3}0.000{col 85}{space 4}-.0710945{col 98}{space 3}-.0233009
{txt}{space 43} {c |}
{space 11}women_het#c.ln_ratio_fmsup_fmsub {c |}
{space 41}1  {c |}{col 45}{res}{space 2} .0012015{col 57}{space 2} .0273455{col 68}{space 1}    0.04{col 77}{space 3}0.965{col 85}{space 4}-.0530256{col 98}{space 3} .0554287
{txt}{space 41}2  {c |}{col 45}{res}{space 2}  .016887{col 57}{space 2}  .031537{col 68}{space 1}    0.54{col 77}{space 3}0.593{col 85}{space 4}-.0456521{col 98}{space 3} .0794261
{txt}{space 43} {c |}
{space 31}1.supervisor {c |}{col 45}{res}{space 2} .1747746{col 57}{space 2} .0183851{col 68}{space 1}    9.51{col 77}{space 3}0.000{col 85}{space 4} .1383162{col 98}{space 3} .2112329
{txt}{space 43} {c |}
{space 10}supervisor#c.ln_ratio_fmsup_fmsub {c |}
{space 41}1  {c |}{col 45}{res}{space 2} .0256508{col 57}{space 2}  .036719{col 68}{space 1}    0.70{col 77}{space 3}0.486{col 85}{space 4}-.0471644{col 98}{space 3}  .098466
{txt}{space 43} {c |}
{space 23}women_het#supervisor {c |}
{space 39}1 1  {c |}{col 45}{res}{space 2} .0120552{col 57}{space 2} .0123703{col 68}{space 1}    0.97{col 77}{space 3}0.332{col 85}{space 4}-.0124755{col 98}{space 3} .0365859
{txt}{space 39}2 1  {c |}{col 45}{res}{space 2}-.0058496{col 57}{space 2} .0219064{col 68}{space 1}   -0.27{col 77}{space 3}0.790{col 85}{space 4}-.0492908{col 98}{space 3} .0375917
{txt}{space 43} {c |}
women_het#supervisor#c.ln_ratio_fmsup_fmsub {c |}
{space 39}1 1  {c |}{col 45}{res}{space 2} .0240872{col 57}{space 2} .0266503{col 68}{space 1}    0.90{col 77}{space 3}0.368{col 85}{space 4}-.0287612{col 98}{space 3} .0769357
{txt}{space 39}2 1  {c |}{col 45}{res}{space 2}-.0042925{col 57}{space 2} .0408439{col 68}{space 1}   -0.11{col 77}{space 3}0.917{col 85}{space 4}-.0852876{col 98}{space 3} .0767025
{txt}{space 43} {c |}
{space 19}ln_ratio_fem_tot_men_tot {c |}{col 45}{res}{space 2}-.0266705{col 57}{space 2}  .065272{col 68}{space 1}   -0.41{col 77}{space 3}0.684{col 85}{space 4}-.1561075{col 98}{space 3} .1027664
{txt}{space 35}minority {c |}{col 45}{res}{space 2} -.035183{col 57}{space 2} .0041787{col 68}{space 1}   -8.42{col 77}{space 3}0.000{col 85}{space 4}-.0434696{col 98}{space 3}-.0268964
{txt}{space 29}topoffgender_2 {c |}{col 45}{res}{space 2}-.0049894{col 57}{space 2}  .005175{col 68}{space 1}   -0.96{col 77}{space 3}0.337{col 85}{space 4}-.0152516{col 98}{space 3} .0052728
{txt}{space 23}lntotworkforce_count {c |}{col 45}{res}{space 2} .0718616{col 57}{space 2} .0338302{col 68}{space 1}    2.12{col 77}{space 3}0.036{col 85}{space 4} .0047751{col 98}{space 3} .1389482
{txt}{space 15}ln_professionals_total_ratio {c |}{col 45}{res}{space 2} .0165505{col 57}{space 2} .0441104{col 68}{space 1}    0.38{col 77}{space 3}0.708{col 85}{space 4} -.070922{col 98}{space 3}  .104023
{txt}{space 43} {c |}
{space 35}agencyid {c |}
{space 41}2  {c |}{col 45}{res}{space 2} .2910768{col 57}{space 2} .1168111{col 68}{space 1}    2.49{col 77}{space 3}0.014{col 85}{space 4} .0594359{col 98}{space 3} .5227177
{txt}{space 41}3  {c |}{col 45}{res}{space 2} .0291521{col 57}{space 2} .0551069{col 68}{space 1}    0.53{col 77}{space 3}0.598{col 85}{space 4} -.080127{col 98}{space 3} .1384313
{txt}{space 41}4  {c |}{col 45}{res}{space 2} .3932991{col 57}{space 2} .1562855{col 68}{space 1}    2.52{col 77}{space 3}0.013{col 85}{space 4} .0833792{col 98}{space 3} .7032191
{txt}{space 41}5  {c |}{col 45}{res}{space 2} .2448933{col 57}{space 2} .1073313{col 68}{space 1}    2.28{col 77}{space 3}0.025{col 85}{space 4} .0320514{col 98}{space 3} .4577353
{txt}{space 41}6  {c |}{col 45}{res}{space 2} .2028184{col 57}{space 2} .1139937{col 68}{space 1}    1.78{col 77}{space 3}0.078{col 85}{space 4}-.0232355{col 98}{space 3} .4288722
{txt}{space 41}7  {c |}{col 45}{res}{space 2} .3281724{col 57}{space 2} .1885022{col 68}{space 1}    1.74{col 77}{space 3}0.085{col 85}{space 4}-.0456346{col 98}{space 3} .7019794
{txt}{space 41}8  {c |}{col 45}{res}{space 2} .2750627{col 57}{space 2} .1465294{col 68}{space 1}    1.88{col 77}{space 3}0.063{col 85}{space 4}-.0155107{col 98}{space 3} .5656361
{txt}{space 41}9  {c |}{col 45}{res}{space 2} -.011293{col 57}{space 2} .0267225{col 68}{space 1}   -0.42{col 77}{space 3}0.673{col 85}{space 4}-.0642846{col 98}{space 3} .0416987
{txt}{space 40}10  {c |}{col 45}{res}{space 2} .2004174{col 57}{space 2} .1682894{col 68}{space 1}    1.19{col 77}{space 3}0.236{col 85}{space 4}-.1333068{col 98}{space 3} .5341416
{txt}{space 40}11  {c |}{col 45}{res}{space 2} .2095137{col 57}{space 2} .1264577{col 68}{space 1}    1.66{col 77}{space 3}0.101{col 85}{space 4}-.0412566{col 98}{space 3}  .460284
{txt}{space 40}12  {c |}{col 45}{res}{space 2} .4061045{col 57}{space 2}  .177118{col 68}{space 1}    2.29{col 77}{space 3}0.024{col 85}{space 4} .0548728{col 98}{space 3} .7573363
{txt}{space 40}13  {c |}{col 45}{res}{space 2} .3688963{col 57}{space 2} .1483306{col 68}{space 1}    2.49{col 77}{space 3}0.014{col 85}{space 4} .0747511{col 98}{space 3} .6630415
{txt}{space 40}14  {c |}{col 45}{res}{space 2} .1851378{col 57}{space 2} .1093593{col 68}{space 1}    1.69{col 77}{space 3}0.093{col 85}{space 4}-.0317258{col 98}{space 3} .4020014
{txt}{space 40}15  {c |}{col 45}{res}{space 2} .3312779{col 57}{space 2} .1205442{col 68}{space 1}    2.75{col 77}{space 3}0.007{col 85}{space 4} .0922343{col 98}{space 3} .5703215
{txt}{space 40}16  {c |}{col 45}{res}{space 2} .4136031{col 57}{space 2} .2022001{col 68}{space 1}    2.05{col 77}{space 3}0.043{col 85}{space 4} .0126328{col 98}{space 3} .8145734
{txt}{space 40}17  {c |}{col 45}{res}{space 2} .1298635{col 57}{space 2} .1686435{col 68}{space 1}    0.77{col 77}{space 3}0.443{col 85}{space 4} -.204563{col 98}{space 3} .4642899
{txt}{space 40}18  {c |}{col 45}{res}{space 2} .3414268{col 57}{space 2} .1569483{col 68}{space 1}    2.18{col 77}{space 3}0.032{col 85}{space 4} .0301923{col 98}{space 3} .6526612
{txt}{space 40}19  {c |}{col 45}{res}{space 2} .2106775{col 57}{space 2} .1020042{col 68}{space 1}    2.07{col 77}{space 3}0.041{col 85}{space 4} .0083994{col 98}{space 3} .4129557
{txt}{space 40}20  {c |}{col 45}{res}{space 2} .2738058{col 57}{space 2} .1699036{col 68}{space 1}    1.61{col 77}{space 3}0.110{col 85}{space 4}-.0631194{col 98}{space 3}  .610731
{txt}{space 40}21  {c |}{col 45}{res}{space 2} .2607126{col 57}{space 2} .1252574{col 68}{space 1}    2.08{col 77}{space 3}0.040{col 85}{space 4} .0123225{col 98}{space 3} .5091026
{txt}{space 40}22  {c |}{col 45}{res}{space 2} .2761757{col 57}{space 2} .1474211{col 68}{space 1}    1.87{col 77}{space 3}0.064{col 85}{space 4}-.0161659{col 98}{space 3} .5685173
{txt}{space 40}23  {c |}{col 45}{res}{space 2}-.1216444{col 57}{space 2} .0569231{col 68}{space 1}   -2.14{col 77}{space 3}0.035{col 85}{space 4} -.234525{col 98}{space 3}-.0087638
{txt}{space 40}24  {c |}{col 45}{res}{space 2} .2952621{col 57}{space 2} .0996854{col 68}{space 1}    2.96{col 77}{space 3}0.004{col 85}{space 4} .0975822{col 98}{space 3}  .492942
{txt}{space 40}25  {c |}{col 45}{res}{space 2}   .20045{col 57}{space 2}  .145838{col 68}{space 1}    1.37{col 77}{space 3}0.172{col 85}{space 4}-.0887521{col 98}{space 3} .4896522
{txt}{space 40}26  {c |}{col 45}{res}{space 2} .0883923{col 57}{space 2} .1172858{col 68}{space 1}    0.75{col 77}{space 3}0.453{col 85}{space 4}-.1441899{col 98}{space 3} .3209744
{txt}{space 40}27  {c |}{col 45}{res}{space 2} .3076514{col 57}{space 2} .1650543{col 68}{space 1}    1.86{col 77}{space 3}0.065{col 85}{space 4}-.0196574{col 98}{space 3} .6349603
{txt}{space 40}28  {c |}{col 45}{res}{space 2}-.0364466{col 57}{space 2} .0766459{col 68}{space 1}   -0.48{col 77}{space 3}0.635{col 85}{space 4}-.1884383{col 98}{space 3} .1155452
{txt}{space 40}29  {c |}{col 45}{res}{space 2} .0842801{col 57}{space 2} .1377445{col 68}{space 1}    0.61{col 77}{space 3}0.542{col 85}{space 4}-.1888724{col 98}{space 3} .3574326
{txt}{space 40}30  {c |}{col 45}{res}{space 2} .0928261{col 57}{space 2} .1307171{col 68}{space 1}    0.71{col 77}{space 3}0.479{col 85}{space 4}-.1663908{col 98}{space 3} .3520429
{txt}{space 40}31  {c |}{col 45}{res}{space 2}  -.08253{col 57}{space 2}  .156658{col 68}{space 1}   -0.53{col 77}{space 3}0.599{col 85}{space 4}-.3931887{col 98}{space 3} .2281287
{txt}{space 40}32  {c |}{col 45}{res}{space 2} .2399991{col 57}{space 2} .1167935{col 68}{space 1}    2.05{col 77}{space 3}0.042{col 85}{space 4} .0083933{col 98}{space 3} .4716049
{txt}{space 40}33  {c |}{col 45}{res}{space 2} .1410693{col 57}{space 2}  .071743{col 68}{space 1}    1.97{col 77}{space 3}0.052{col 85}{space 4}-.0011999{col 98}{space 3} .2833384
{txt}{space 40}34  {c |}{col 45}{res}{space 2} .1345957{col 57}{space 2} .1231288{col 68}{space 1}    1.09{col 77}{space 3}0.277{col 85}{space 4}-.1095733{col 98}{space 3} .3787648
{txt}{space 40}35  {c |}{col 45}{res}{space 2} .1608869{col 57}{space 2} .0965074{col 68}{space 1}    1.67{col 77}{space 3}0.099{col 85}{space 4} -.030491{col 98}{space 3} .3522647
{txt}{space 40}36  {c |}{col 45}{res}{space 2} .2151164{col 57}{space 2} .1221289{col 68}{space 1}    1.76{col 77}{space 3}0.081{col 85}{space 4}-.0270697{col 98}{space 3} .4573025
{txt}{space 40}37  {c |}{col 45}{res}{space 2} .2267397{col 57}{space 2} .1144639{col 68}{space 1}    1.98{col 77}{space 3}0.050{col 85}{space 4}-.0002466{col 98}{space 3} .4537259
{txt}{space 40}38  {c |}{col 45}{res}{space 2}   .34951{col 57}{space 2} .1679855{col 68}{space 1}    2.08{col 77}{space 3}0.040{col 85}{space 4} .0163884{col 98}{space 3} .6826316
{txt}{space 40}39  {c |}{col 45}{res}{space 2} .2618258{col 57}{space 2} .1189192{col 68}{space 1}    2.20{col 77}{space 3}0.030{col 85}{space 4} .0260045{col 98}{space 3} .4976471
{txt}{space 40}40  {c |}{col 45}{res}{space 2} .0264401{col 57}{space 2} .0750243{col 68}{space 1}    0.35{col 77}{space 3}0.725{col 85}{space 4}-.1223359{col 98}{space 3} .1752162
{txt}{space 40}41  {c |}{col 45}{res}{space 2}  .305866{col 57}{space 2} .1524873{col 68}{space 1}    2.01{col 77}{space 3}0.047{col 85}{space 4}  .003478{col 98}{space 3}  .608254
{txt}{space 40}42  {c |}{col 45}{res}{space 2} .2981258{col 57}{space 2} .1269939{col 68}{space 1}    2.35{col 77}{space 3}0.021{col 85}{space 4} .0462921{col 98}{space 3} .5499594
{txt}{space 40}43  {c |}{col 45}{res}{space 2} .0280127{col 57}{space 2} .0496476{col 68}{space 1}    0.56{col 77}{space 3}0.574{col 85}{space 4}-.0704405{col 98}{space 3} .1264658
{txt}{space 40}44  {c |}{col 45}{res}{space 2} .3475502{col 57}{space 2} .1066266{col 68}{space 1}    3.26{col 77}{space 3}0.002{col 85}{space 4} .1361057{col 98}{space 3} .5589947
{txt}{space 40}45  {c |}{col 45}{res}{space 2} .3233104{col 57}{space 2} .1275037{col 68}{space 1}    2.54{col 77}{space 3}0.013{col 85}{space 4} .0704657{col 98}{space 3}  .576155
{txt}{space 40}46  {c |}{col 45}{res}{space 2} .2975664{col 57}{space 2}  .193797{col 68}{space 1}    1.54{col 77}{space 3}0.128{col 85}{space 4}-.0867403{col 98}{space 3} .6818731
{txt}{space 40}47  {c |}{col 45}{res}{space 2} .1851583{col 57}{space 2}  .091931{col 68}{space 1}    2.01{col 77}{space 3}0.047{col 85}{space 4} .0028557{col 98}{space 3}  .367461
{txt}{space 40}48  {c |}{col 45}{res}{space 2} .2010215{col 57}{space 2} .1428012{col 68}{space 1}    1.41{col 77}{space 3}0.162{col 85}{space 4}-.0821587{col 98}{space 3} .4842017
{txt}{space 40}49  {c |}{col 45}{res}{space 2} .4717767{col 57}{space 2} .1971349{col 68}{space 1}    2.39{col 77}{space 3}0.018{col 85}{space 4} .0808507{col 98}{space 3} .8627026
{txt}{space 40}50  {c |}{col 45}{res}{space 2} .4377358{col 57}{space 2} .1637745{col 68}{space 1}    2.67{col 77}{space 3}0.009{col 85}{space 4} .1129647{col 98}{space 3} .7625069
{txt}{space 40}51  {c |}{col 45}{res}{space 2}  .385559{col 57}{space 2}  .197775{col 68}{space 1}    1.95{col 77}{space 3}0.054{col 85}{space 4}-.0066363{col 98}{space 3} .7777543
{txt}{space 40}52  {c |}{col 45}{res}{space 2} .3277868{col 57}{space 2}  .188318{col 68}{space 1}    1.74{col 77}{space 3}0.085{col 85}{space 4} -.045655{col 98}{space 3} .7012285
{txt}{space 40}53  {c |}{col 45}{res}{space 2} .2579833{col 57}{space 2} .1432933{col 68}{space 1}    1.80{col 77}{space 3}0.075{col 85}{space 4}-.0261727{col 98}{space 3} .5421392
{txt}{space 40}54  {c |}{col 45}{res}{space 2} .3214472{col 57}{space 2} .1575878{col 68}{space 1}    2.04{col 77}{space 3}0.044{col 85}{space 4} .0089447{col 98}{space 3} .6339498
{txt}{space 40}55  {c |}{col 45}{res}{space 2} .5145536{col 57}{space 2} .2189044{col 68}{space 1}    2.35{col 77}{space 3}0.021{col 85}{space 4} .0804579{col 98}{space 3} .9486493
{txt}{space 40}56  {c |}{col 45}{res}{space 2} .3137743{col 57}{space 2} .2101528{col 68}{space 1}    1.49{col 77}{space 3}0.138{col 85}{space 4}-.1029665{col 98}{space 3} .7305152
{txt}{space 40}57  {c |}{col 45}{res}{space 2} .4289762{col 57}{space 2} .2446263{col 68}{space 1}    1.75{col 77}{space 3}0.082{col 85}{space 4}-.0561269{col 98}{space 3} .9140794
{txt}{space 40}58  {c |}{col 45}{res}{space 2} .2843916{col 57}{space 2} .1561799{col 68}{space 1}    1.82{col 77}{space 3}0.071{col 85}{space 4} -.025319{col 98}{space 3} .5941022
{txt}{space 40}59  {c |}{col 45}{res}{space 2} .2959128{col 57}{space 2} .1770294{col 68}{space 1}    1.67{col 77}{space 3}0.098{col 85}{space 4}-.0551431{col 98}{space 3} .6469686
{txt}{space 40}60  {c |}{col 45}{res}{space 2} .1710154{col 57}{space 2} .0959599{col 68}{space 1}    1.78{col 77}{space 3}0.078{col 85}{space 4}-.0192768{col 98}{space 3} .3613075
{txt}{space 40}61  {c |}{col 45}{res}{space 2} .1790856{col 57}{space 2} .1101561{col 68}{space 1}    1.63{col 77}{space 3}0.107{col 85}{space 4} -.039358{col 98}{space 3} .3975293
{txt}{space 40}62  {c |}{col 45}{res}{space 2} .3955741{col 57}{space 2} .1774679{col 68}{space 1}    2.23{col 77}{space 3}0.028{col 85}{space 4} .0436485{col 98}{space 3} .7474996
{txt}{space 40}63  {c |}{col 45}{res}{space 2}   .44528{col 57}{space 2}  .176271{col 68}{space 1}    2.53{col 77}{space 3}0.013{col 85}{space 4} .0957281{col 98}{space 3} .7948319
{txt}{space 40}64  {c |}{col 45}{res}{space 2} .5316794{col 57}{space 2} .1915612{col 68}{space 1}    2.78{col 77}{space 3}0.007{col 85}{space 4} .1518063{col 98}{space 3} .9115525
{txt}{space 40}65  {c |}{col 45}{res}{space 2} .2762332{col 57}{space 2}  .106069{col 68}{space 1}    2.60{col 77}{space 3}0.011{col 85}{space 4} .0658945{col 98}{space 3} .4865719
{txt}{space 40}66  {c |}{col 45}{res}{space 2} .3447355{col 57}{space 2} .2109328{col 68}{space 1}    1.63{col 77}{space 3}0.105{col 85}{space 4}-.0735521{col 98}{space 3} .7630232
{txt}{space 40}67  {c |}{col 45}{res}{space 2} .3303676{col 57}{space 2} .1375045{col 68}{space 1}    2.40{col 77}{space 3}0.018{col 85}{space 4}  .057691{col 98}{space 3} .6030442
{txt}{space 40}68  {c |}{col 45}{res}{space 2} .3297216{col 57}{space 2} .1568033{col 68}{space 1}    2.10{col 77}{space 3}0.038{col 85}{space 4} .0187747{col 98}{space 3} .6406684
{txt}{space 40}69  {c |}{col 45}{res}{space 2} .1810248{col 57}{space 2} .1187627{col 68}{space 1}    1.52{col 77}{space 3}0.130{col 85}{space 4}-.0544861{col 98}{space 3} .4165357
{txt}{space 40}70  {c |}{col 45}{res}{space 2} .4341964{col 57}{space 2} .1961666{col 68}{space 1}    2.21{col 77}{space 3}0.029{col 85}{space 4} .0451906{col 98}{space 3} .8232023
{txt}{space 40}71  {c |}{col 45}{res}{space 2} .1388197{col 57}{space 2} .1469235{col 68}{space 1}    0.94{col 77}{space 3}0.347{col 85}{space 4}-.1525351{col 98}{space 3} .4301745
{txt}{space 40}72  {c |}{col 45}{res}{space 2} .2761298{col 57}{space 2} .1167303{col 68}{space 1}    2.37{col 77}{space 3}0.020{col 85}{space 4} .0446492{col 98}{space 3} .5076104
{txt}{space 40}73  {c |}{col 45}{res}{space 2} .5073516{col 57}{space 2} .1731962{col 68}{space 1}    2.93{col 77}{space 3}0.004{col 85}{space 4} .1638971{col 98}{space 3} .8508062
{txt}{space 40}74  {c |}{col 45}{res}{space 2} .0874994{col 57}{space 2} .1124341{col 68}{space 1}    0.78{col 77}{space 3}0.438{col 85}{space 4}-.1354617{col 98}{space 3} .3104604
{txt}{space 40}75  {c |}{col 45}{res}{space 2} .1965829{col 57}{space 2} .1339347{col 68}{space 1}    1.47{col 77}{space 3}0.145{col 85}{space 4}-.0690146{col 98}{space 3} .4621803
{txt}{space 40}76  {c |}{col 45}{res}{space 2}  .312344{col 57}{space 2} .1591949{col 68}{space 1}    1.96{col 77}{space 3}0.052{col 85}{space 4}-.0033455{col 98}{space 3} .6280335
{txt}{space 40}77  {c |}{col 45}{res}{space 2} .2857648{col 57}{space 2} .1505046{col 68}{space 1}    1.90{col 77}{space 3}0.060{col 85}{space 4}-.0126914{col 98}{space 3}  .584221
{txt}{space 40}78  {c |}{col 45}{res}{space 2} .2941811{col 57}{space 2} .1021764{col 68}{space 1}    2.88{col 77}{space 3}0.005{col 85}{space 4} .0915614{col 98}{space 3} .4968008
{txt}{space 40}79  {c |}{col 45}{res}{space 2}-.0206174{col 57}{space 2} .0174291{col 68}{space 1}   -1.18{col 77}{space 3}0.240{col 85}{space 4}  -.05518{col 98}{space 3} .0139451
{txt}{space 40}80  {c |}{col 45}{res}{space 2} .4355245{col 57}{space 2} .1796745{col 68}{space 1}    2.42{col 77}{space 3}0.017{col 85}{space 4} .0792231{col 98}{space 3} .7918258
{txt}{space 40}81  {c |}{col 45}{res}{space 2} .2347638{col 57}{space 2} .1840485{col 68}{space 1}    1.28{col 77}{space 3}0.205{col 85}{space 4}-.1302113{col 98}{space 3}  .599739
{txt}{space 40}82  {c |}{col 45}{res}{space 2} .3421269{col 57}{space 2} .1894505{col 68}{space 1}    1.81{col 77}{space 3}0.074{col 85}{space 4}-.0335606{col 98}{space 3} .7178145
{txt}{space 40}83  {c |}{col 45}{res}{space 2} .4032678{col 57}{space 2} .1495635{col 68}{space 1}    2.70{col 77}{space 3}0.008{col 85}{space 4} .1066777{col 98}{space 3} .6998579
{txt}{space 40}84  {c |}{col 45}{res}{space 2} .3610562{col 57}{space 2} .1906111{col 68}{space 1}    1.89{col 77}{space 3}0.061{col 85}{space 4}-.0169327{col 98}{space 3} .7390451
{txt}{space 40}85  {c |}{col 45}{res}{space 2} .4370163{col 57}{space 2} .1543843{col 68}{space 1}    2.83{col 77}{space 3}0.006{col 85}{space 4} .1308665{col 98}{space 3} .7431661
{txt}{space 40}86  {c |}{col 45}{res}{space 2} .4372929{col 57}{space 2} .1947209{col 68}{space 1}    2.25{col 77}{space 3}0.027{col 85}{space 4}  .051154{col 98}{space 3} .8234317
{txt}{space 40}87  {c |}{col 45}{res}{space 2} .4918902{col 57}{space 2} .1973449{col 68}{space 1}    2.49{col 77}{space 3}0.014{col 85}{space 4} .1005478{col 98}{space 3} .8832325
{txt}{space 40}88  {c |}{col 45}{res}{space 2} .2411892{col 57}{space 2} .1401337{col 68}{space 1}    1.72{col 77}{space 3}0.088{col 85}{space 4}-.0367012{col 98}{space 3} .5190797
{txt}{space 40}89  {c |}{col 45}{res}{space 2} .2783133{col 57}{space 2} .1497319{col 68}{space 1}    1.86{col 77}{space 3}0.066{col 85}{space 4}-.0186106{col 98}{space 3} .5752372
{txt}{space 40}90  {c |}{col 45}{res}{space 2} .0990265{col 57}{space 2} .1226529{col 68}{space 1}    0.81{col 77}{space 3}0.421{col 85}{space 4}-.1441989{col 98}{space 3} .3422518
{txt}{space 40}91  {c |}{col 45}{res}{space 2} .1918503{col 57}{space 2} .1136538{col 68}{space 1}    1.69{col 77}{space 3}0.094{col 85}{space 4}-.0335295{col 98}{space 3} .4172301
{txt}{space 40}92  {c |}{col 45}{res}{space 2} .0808121{col 57}{space 2}  .048716{col 68}{space 1}    1.66{col 77}{space 3}0.100{col 85}{space 4}-.0157934{col 98}{space 3} .1774177
{txt}{space 40}93  {c |}{col 45}{res}{space 2} .4213535{col 57}{space 2} .1508739{col 68}{space 1}    2.79{col 77}{space 3}0.006{col 85}{space 4} .1221649{col 98}{space 3}  .720542
{txt}{space 40}94  {c |}{col 45}{res}{space 2} .4467453{col 57}{space 2} .1757091{col 68}{space 1}    2.54{col 77}{space 3}0.012{col 85}{space 4} .0983075{col 98}{space 3} .7951831
{txt}{space 40}95  {c |}{col 45}{res}{space 2} .1698064{col 57}{space 2} .1534702{col 68}{space 1}    1.11{col 77}{space 3}0.271{col 85}{space 4}-.1345308{col 98}{space 3} .4741436
{txt}{space 40}96  {c |}{col 45}{res}{space 2}  .358582{col 57}{space 2} .1584996{col 68}{space 1}    2.26{col 77}{space 3}0.026{col 85}{space 4} .0442713{col 98}{space 3} .6728928
{txt}{space 40}97  {c |}{col 45}{res}{space 2} .3993567{col 57}{space 2}  .153485{col 68}{space 1}    2.60{col 77}{space 3}0.011{col 85}{space 4} .0949901{col 98}{space 3} .7037233
{txt}{space 40}98  {c |}{col 45}{res}{space 2} .5577411{col 57}{space 2} .1892091{col 68}{space 1}    2.95{col 77}{space 3}0.004{col 85}{space 4} .1825322{col 98}{space 3} .9329499
{txt}{space 40}99  {c |}{col 45}{res}{space 2} .1232799{col 57}{space 2} .1042527{col 68}{space 1}    1.18{col 77}{space 3}0.240{col 85}{space 4}-.0834572{col 98}{space 3}  .330017
{txt}{space 39}100  {c |}{col 45}{res}{space 2} .2034753{col 57}{space 2} .1558167{col 68}{space 1}    1.31{col 77}{space 3}0.194{col 85}{space 4} -.105515{col 98}{space 3} .5124657
{txt}{space 39}101  {c |}{col 45}{res}{space 2} .4180207{col 57}{space 2} .1388847{col 68}{space 1}    3.01{col 77}{space 3}0.003{col 85}{space 4} .1426072{col 98}{space 3} .6934343
{txt}{space 39}102  {c |}{col 45}{res}{space 2} .2754927{col 57}{space 2} .1645217{col 68}{space 1}    1.67{col 77}{space 3}0.097{col 85}{space 4}-.0507601{col 98}{space 3} .6017454
{txt}{space 39}103  {c |}{col 45}{res}{space 2} .0901571{col 57}{space 2} .1125394{col 68}{space 1}    0.80{col 77}{space 3}0.425{col 85}{space 4}-.1330129{col 98}{space 3}  .313327
{txt}{space 39}104  {c |}{col 45}{res}{space 2}-.0983284{col 57}{space 2} .0893558{col 68}{space 1}   -1.10{col 77}{space 3}0.274{col 85}{space 4}-.2755242{col 98}{space 3} .0788674
{txt}{space 39}105  {c |}{col 45}{res}{space 2} .3369314{col 57}{space 2} .1574753{col 68}{space 1}    2.14{col 77}{space 3}0.035{col 85}{space 4} .0246519{col 98}{space 3} .6492109
{txt}{space 43} {c |}
{space 39}year {c |}
{space 38}2011  {c |}{col 45}{res}{space 2}-.0031019{col 57}{space 2} .0033559{col 68}{space 1}   -0.92{col 77}{space 3}0.357{col 85}{space 4}-.0097568{col 98}{space 3} .0035529
{txt}{space 38}2012  {c |}{col 45}{res}{space 2}   .00705{col 57}{space 2} .0053423{col 68}{space 1}    1.32{col 77}{space 3}0.190{col 85}{space 4} -.003544{col 98}{space 3}  .017644
{txt}{space 38}2013  {c |}{col 45}{res}{space 2} .0098085{col 57}{space 2}  .005987{col 68}{space 1}    1.64{col 77}{space 3}0.104{col 85}{space 4} -.002064{col 98}{space 3}  .021681
{txt}{space 38}2014  {c |}{col 45}{res}{space 2} .0091141{col 57}{space 2} .0081558{col 68}{space 1}    1.12{col 77}{space 3}0.266{col 85}{space 4}-.0070591{col 98}{space 3} .0252874
{txt}{space 38}2015  {c |}{col 45}{res}{space 2} .0035016{col 57}{space 2} .0096826{col 68}{space 1}    0.36{col 77}{space 3}0.718{col 85}{space 4}-.0156994{col 98}{space 3} .0227027
{txt}{space 38}2016  {c |}{col 45}{res}{space 2} .0011291{col 57}{space 2} .0082902{col 68}{space 1}    0.14{col 77}{space 3}0.892{col 85}{space 4}-.0153106{col 98}{space 3} .0175688
{txt}{space 38}2017  {c |}{col 45}{res}{space 2} .0089713{col 57}{space 2} .0112299{col 68}{space 1}    0.80{col 77}{space 3}0.426{col 85}{space 4}-.0132979{col 98}{space 3} .0312405
{txt}{space 38}2018  {c |}{col 45}{res}{space 2}-.0212366{col 57}{space 2} .0089201{col 68}{space 1}   -2.38{col 77}{space 3}0.019{col 85}{space 4}-.0389255{col 98}{space 3}-.0035476
{txt}{space 38}2019  {c |}{col 45}{res}{space 2}-.0517478{col 57}{space 2} .0099001{col 68}{space 1}   -5.23{col 77}{space 3}0.000{col 85}{space 4}  -.07138{col 98}{space 3}-.0321155
{txt}{space 43} {c |}
{space 38}_cons {c |}{col 45}{res}{space 2} .0240315{col 57}{space 2} .4296912{col 68}{space 1}    0.06{col 77}{space 3}0.956{col 85}{space 4}-.8280623{col 98}{space 3} .8761254
{txt}{hline 44}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1984008{col 39} -1921960{col 50}    25{col 58}  3843970{col 69}  3844289
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. ** BY NON-SUPERVISORS RESPONDENT: BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN GENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1237888{col 26}{space 2} .0501231{col 37}{space 1}    2.47{col 46}{space 3}0.015{col 54}{space 4} .0243928{col 67}{space 3} .2231847
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.women_het#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.women_het#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0012015{col 26}{space 2} .0273455{col 37}{space 1}    0.04{col 46}{space 3}0.965{col 54}{space 4}-.0530256{col 67}{space 3} .0554287
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.women_het#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.women_het#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}  .016887{col 26}{space 2}  .031537{col 37}{space 1}    0.54{col 46}{space 3}0.593{col 54}{space 4}-.0456521{col 67}{space 3} .0794261
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. lincom 2.women_het#c.ln_ratio_fmsup_fmsub -  1.women_het#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.women_het#c.ln_ratio_fmsup_fmsub + 2.women_het#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0156855{col 26}{space 2} .0193727{col 37}{space 1}    0.81{col 46}{space 3}0.420{col 54}{space 4}-.0227314{col 67}{space 3} .0541023
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. 
. 
. ** BY SUPERVISOR RESPONDENT:BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEENGENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fmsup_fmsub + 1.supervisor#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fmsup_fmsub + 1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1494395{col 26}{space 2}  .050458{col 37}{space 1}    2.96{col 46}{space 3}0.004{col 54}{space 4} .0493795{col 67}{space 3} .2494996
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.women_het#c.ln_ratio_fmsup_fmsub +  1.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.women_het#c.ln_ratio_fmsup_fmsub + 1.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0252888{col 26}{space 2} .0208764{col 37}{space 1}    1.21{col 46}{space 3}0.229{col 54}{space 4}-.0161099{col 67}{space 3} .0666875
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.women_het#c.ln_ratio_fmsup_fmsub +  2.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.women_het#c.ln_ratio_fmsup_fmsub + 2.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0125945{col 26}{space 2} .0324242{col 37}{space 1}    0.39{col 46}{space 3}0.698{col 54}{space 4}-.0517039{col 67}{space 3} .0768929
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. lincom  2.women_het#c.ln_ratio_fmsup_fmsub +  2.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub - (1.women_het#c.ln_ratio_fmsup_fmsub +  1.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub)

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.women_het#c.ln_ratio_fmsup_fmsub + 2.women_het#c.ln_ratio_fmsup_fmsub - 1.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub + 2.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0126943{col 26}{space 2} .0278776{col 37}{space 1}   -0.46{col 46}{space 3}0.650{col 54}{space 4}-.0679766{col 67}{space 3}  .042588
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. * SUPERVISOR - NON-SUPERVISORY DIFFERENCE AMONG WOMEN RESPONDENT DIFFERENCES [NON-MINORITY WOMEN RESPONDENTS FOLLOWED BY MINORITY WOMEN RESPONDENTS] -- DO NOT PLOT IN GRAPHS [ONLY FOR TEXT]!
. 
. lincom  1.women_het#c.ln_ratio_fmsup_fmsub +  1.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub  - (1.women_het#c.ln_ratio_fmsup_fmsub)

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0240872{col 26}{space 2} .0266503{col 37}{space 1}    0.90{col 46}{space 3}0.368{col 54}{space 4}-.0287612{col 67}{space 3} .0769357
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. lincom  2.women_het#c.ln_ratio_fmsup_fmsub +  2.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub  - (2.women_het#c.ln_ratio_fmsup_fmsub)

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0042925{col 26}{space 2} .0408439{col 37}{space 1}   -0.11{col 46}{space 3}0.917{col 54}{space 4}-.0852876{col 67}{space 3} .0767025
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. 
. 
. 
.    
. *** MODEL E8: CONDITIONAL RESPONSES BY RACE/ETHNICITY & POSITION -- RACIAL/ETHNIC BETWEEN-IDENTITY GROUP STATUS DIFFERENTIAL MODEL: [MINORITY SUPERVISORS WITHIN AGENCY j IN YEAR t / NON-MINORITY SUPERVISORS WITHIN AGENCY j IN YEAR t] / [MINORITY NON-SUPERVISORS WITHIN AGENCY j IN YEAR t / NON-MINORITY NON-SUPERVISORS WITHIN AGENCY j IN YEAR t] -- CONTROLLING FOR RACIAL/ETHNIC SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL  ***
. 
. regress  lnjustice2zeroadj   c.ln_ratio_mnmsup_mnmsub##i.minority_het##i.supervisor  ln_ratio_min_tot_nmin_tot   gender  topoffminority_2 lntotworkforce_count  ln_professionals_total_ratio   i.agencyid i.year if e(sample), vce(cluster agencyid)

{txt}Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(24, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0483
                                                {txt}Root MSE          =    {res} .52085

{txt}{ralign 114:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 49}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 50}{c |}{col 62}    Robust
{col 1}                               lnjustice2zeroadj{col 50}{c |} Coefficient{col 62}  std. err.{col 74}      t{col 82}   P>|t|{col 90}     [95% con{col 103}f. interval]
{hline 49}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 26}ln_ratio_mnmsup_mnmsub {c |}{col 50}{res}{space 2} .0604503{col 62}{space 2} .0358996{col 73}{space 1}    1.68{col 82}{space 3}0.095{col 90}{space 4}  -.01074{col 103}{space 3} .1316406
{txt}{space 48} {c |}
{space 36}minority_het {c |}
{space 46}1  {c |}{col 50}{res}{space 2}-.0240364{col 62}{space 2} .0076095{col 73}{space 1}   -3.16{col 82}{space 3}0.002{col 90}{space 4}-.0391263{col 103}{space 3}-.0089466
{txt}{space 46}2  {c |}{col 50}{res}{space 2}-.0503759{col 62}{space 2} .0098607{col 73}{space 1}   -5.11{col 82}{space 3}0.000{col 90}{space 4}  -.06993{col 103}{space 3}-.0308219
{txt}{space 48} {c |}
{space 11}minority_het#c.ln_ratio_mnmsup_mnmsub {c |}
{space 46}1  {c |}{col 50}{res}{space 2} .0176347{col 62}{space 2} .0175638{col 73}{space 1}    1.00{col 82}{space 3}0.318{col 90}{space 4}-.0171951{col 103}{space 3} .0524644
{txt}{space 46}2  {c |}{col 50}{res}{space 2} .0533415{col 62}{space 2} .0248668{col 73}{space 1}    2.15{col 82}{space 3}0.034{col 90}{space 4} .0040296{col 103}{space 3} .1026534
{txt}{space 48} {c |}
{space 36}1.supervisor {c |}{col 50}{res}{space 2} .1644386{col 62}{space 2} .0143427{col 73}{space 1}   11.46{col 82}{space 3}0.000{col 90}{space 4} .1359965{col 103}{space 3} .1928807
{txt}{space 48} {c |}
{space 13}supervisor#c.ln_ratio_mnmsup_mnmsub {c |}
{space 46}1  {c |}{col 50}{res}{space 2}-.0180699{col 62}{space 2} .0288727{col 73}{space 1}   -0.63{col 82}{space 3}0.533{col 90}{space 4}-.0753255{col 103}{space 3} .0391857
{txt}{space 48} {c |}
{space 25}minority_het#supervisor {c |}
{space 44}1 1  {c |}{col 50}{res}{space 2}-.0050019{col 62}{space 2} .0066602{col 73}{space 1}   -0.75{col 82}{space 3}0.454{col 90}{space 4}-.0182093{col 103}{space 3} .0082056
{txt}{space 44}2 1  {c |}{col 50}{res}{space 2}-.0054936{col 62}{space 2} .0174186{col 73}{space 1}   -0.32{col 82}{space 3}0.753{col 90}{space 4}-.0400355{col 103}{space 3} .0290482
{txt}{space 48} {c |}
minority_het#supervisor#c.ln_ratio_mnmsup_mnmsub {c |}
{space 44}1 1  {c |}{col 50}{res}{space 2} .0487909{col 62}{space 2} .0134158{col 73}{space 1}    3.64{col 82}{space 3}0.000{col 90}{space 4} .0221868{col 103}{space 3} .0753951
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{txt}{space 48} {c |}
{space 23}ln_ratio_min_tot_nmin_tot {c |}{col 50}{res}{space 2} .0226756{col 62}{space 2} .0501008{col 73}{space 1}    0.45{col 82}{space 3}0.652{col 90}{space 4}-.0766762{col 103}{space 3} .1220275
{txt}{space 42}gender {c |}{col 50}{res}{space 2}-.0174375{col 62}{space 2}  .005324{col 73}{space 1}   -3.28{col 82}{space 3}0.001{col 90}{space 4}-.0279952{col 103}{space 3}-.0068798
{txt}{space 32}topoffminority_2 {c |}{col 50}{res}{space 2}  .007209{col 62}{space 2} .0071607{col 73}{space 1}    1.01{col 82}{space 3}0.316{col 90}{space 4}-.0069909{col 103}{space 3} .0214089
{txt}{space 28}lntotworkforce_count {c |}{col 50}{res}{space 2} .0639901{col 62}{space 2} .0408885{col 73}{space 1}    1.56{col 82}{space 3}0.121{col 90}{space 4}-.0170934{col 103}{space 3} .1450736
{txt}{space 20}ln_professionals_total_ratio {c |}{col 50}{res}{space 2} .0250088{col 62}{space 2}  .049843{col 73}{space 1}    0.50{col 82}{space 3}0.617{col 90}{space 4}-.0738317{col 103}{space 3} .1238493
{txt}{space 48} {c |}
{space 40}agencyid {c |}
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{txt}{space 46}4  {c |}{col 50}{res}{space 2} .2268224{col 62}{space 2} .1639619{col 73}{space 1}    1.38{col 82}{space 3}0.170{col 90}{space 4}-.0983201{col 103}{space 3} .5519649
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{txt}{space 46}6  {c |}{col 50}{res}{space 2} .1213025{col 62}{space 2}  .122893{col 73}{space 1}    0.99{col 82}{space 3}0.326{col 90}{space 4} -.122399{col 103}{space 3}  .365004
{txt}{space 46}7  {c |}{col 50}{res}{space 2} .2343108{col 62}{space 2} .2162749{col 73}{space 1}    1.08{col 82}{space 3}0.281{col 90}{space 4}-.1945705{col 103}{space 3}  .663192
{txt}{space 46}8  {c |}{col 50}{res}{space 2} .2096038{col 62}{space 2} .1647665{col 73}{space 1}    1.27{col 82}{space 3}0.206{col 90}{space 4}-.1171344{col 103}{space 3}  .536342
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{txt}{space 45}73  {c |}{col 50}{res}{space 2} .4460479{col 62}{space 2} .1970449{col 73}{space 1}    2.26{col 82}{space 3}0.026{col 90}{space 4} .0553005{col 103}{space 3} .8367953
{txt}{space 45}74  {c |}{col 50}{res}{space 2} .1140904{col 62}{space 2} .1082786{col 73}{space 1}    1.05{col 82}{space 3}0.294{col 90}{space 4}-.1006301{col 103}{space 3}  .328811
{txt}{space 45}75  {c |}{col 50}{res}{space 2} .0914153{col 62}{space 2} .1493058{col 73}{space 1}    0.61{col 82}{space 3}0.542{col 90}{space 4}-.2046637{col 103}{space 3} .3874942
{txt}{space 45}76  {c |}{col 50}{res}{space 2} .2776777{col 62}{space 2} .1807515{col 73}{space 1}    1.54{col 82}{space 3}0.128{col 90}{space 4}-.0807594{col 103}{space 3} .6361148
{txt}{space 45}77  {c |}{col 50}{res}{space 2} .2433579{col 62}{space 2} .1717503{col 73}{space 1}    1.42{col 82}{space 3}0.159{col 90}{space 4}-.0972294{col 103}{space 3} .5839452
{txt}{space 45}78  {c |}{col 50}{res}{space 2} .2731197{col 62}{space 2} .1140977{col 73}{space 1}    2.39{col 82}{space 3}0.018{col 90}{space 4} .0468597{col 103}{space 3} .4993797
{txt}{space 45}79  {c |}{col 50}{res}{space 2}-.0139311{col 62}{space 2} .0261028{col 73}{space 1}   -0.53{col 82}{space 3}0.595{col 90}{space 4} -.065694{col 103}{space 3} .0378317
{txt}{space 45}80  {c |}{col 50}{res}{space 2} .4258806{col 62}{space 2}  .217341{col 73}{space 1}    1.96{col 82}{space 3}0.053{col 90}{space 4}-.0051148{col 103}{space 3}  .856876
{txt}{space 45}81  {c |}{col 50}{res}{space 2} .2040282{col 62}{space 2} .2365748{col 73}{space 1}    0.86{col 82}{space 3}0.390{col 90}{space 4}-.2651085{col 103}{space 3}  .673165
{txt}{space 45}82  {c |}{col 50}{res}{space 2} .2308907{col 62}{space 2} .2082705{col 73}{space 1}    1.11{col 82}{space 3}0.270{col 90}{space 4}-.1821174{col 103}{space 3} .6438988
{txt}{space 45}83  {c |}{col 50}{res}{space 2} .3383488{col 62}{space 2}  .173837{col 73}{space 1}    1.95{col 82}{space 3}0.054{col 90}{space 4}-.0063764{col 103}{space 3}  .683074
{txt}{space 45}84  {c |}{col 50}{res}{space 2} .3177494{col 62}{space 2} .2110347{col 73}{space 1}    1.51{col 82}{space 3}0.135{col 90}{space 4}-.1007404{col 103}{space 3} .7362392
{txt}{space 45}85  {c |}{col 50}{res}{space 2} .3273798{col 62}{space 2} .1581267{col 73}{space 1}    2.07{col 82}{space 3}0.041{col 90}{space 4} .0138085{col 103}{space 3}  .640951
{txt}{space 45}86  {c |}{col 50}{res}{space 2} .3386508{col 62}{space 2} .2416741{col 73}{space 1}    1.40{col 82}{space 3}0.164{col 90}{space 4}-.1405981{col 103}{space 3} .8178997
{txt}{space 45}87  {c |}{col 50}{res}{space 2} .4242421{col 62}{space 2} .2377862{col 73}{space 1}    1.78{col 82}{space 3}0.077{col 90}{space 4}-.0472968{col 103}{space 3}  .895781
{txt}{space 45}88  {c |}{col 50}{res}{space 2} .1679624{col 62}{space 2} .1666986{col 73}{space 1}    1.01{col 82}{space 3}0.316{col 90}{space 4}-.1626071{col 103}{space 3} .4985319
{txt}{space 45}89  {c |}{col 50}{res}{space 2} .2197876{col 62}{space 2} .1692155{col 73}{space 1}    1.30{col 82}{space 3}0.197{col 90}{space 4}-.1157731{col 103}{space 3} .5553483
{txt}{space 45}90  {c |}{col 50}{res}{space 2} .0358112{col 62}{space 2} .0850231{col 73}{space 1}    0.42{col 82}{space 3}0.674{col 90}{space 4}-.1327929{col 103}{space 3} .2044153
{txt}{space 45}91  {c |}{col 50}{res}{space 2} .1406561{col 62}{space 2}  .119109{col 73}{space 1}    1.18{col 82}{space 3}0.240{col 90}{space 4}-.0955415{col 103}{space 3} .3768538
{txt}{space 45}92  {c |}{col 50}{res}{space 2} .0815633{col 62}{space 2} .0589077{col 73}{space 1}    1.38{col 82}{space 3}0.169{col 90}{space 4}-.0352529{col 103}{space 3} .1983794
{txt}{space 45}93  {c |}{col 50}{res}{space 2} .3630092{col 62}{space 2} .1775661{col 73}{space 1}    2.04{col 82}{space 3}0.043{col 90}{space 4}  .010889{col 103}{space 3} .7151294
{txt}{space 45}94  {c |}{col 50}{res}{space 2} .4464371{col 62}{space 2} .2159586{col 73}{space 1}    2.07{col 82}{space 3}0.041{col 90}{space 4} .0181831{col 103}{space 3} .8746912
{txt}{space 45}95  {c |}{col 50}{res}{space 2} .1606343{col 62}{space 2} .2063096{col 73}{space 1}    0.78{col 82}{space 3}0.438{col 90}{space 4}-.2484855{col 103}{space 3}  .569754
{txt}{space 45}96  {c |}{col 50}{res}{space 2} .3204975{col 62}{space 2} .1908504{col 73}{space 1}    1.68{col 82}{space 3}0.096{col 90}{space 4} -.057966{col 103}{space 3}  .698961
{txt}{space 45}97  {c |}{col 50}{res}{space 2} .3150824{col 62}{space 2}  .156112{col 73}{space 1}    2.02{col 82}{space 3}0.046{col 90}{space 4} .0055063{col 103}{space 3} .6246584
{txt}{space 45}98  {c |}{col 50}{res}{space 2}  .459126{col 62}{space 2} .2263529{col 73}{space 1}    2.03{col 82}{space 3}0.045{col 90}{space 4} .0102598{col 103}{space 3} .9079923
{txt}{space 45}99  {c |}{col 50}{res}{space 2} .0701086{col 62}{space 2} .0572502{col 73}{space 1}    1.22{col 82}{space 3}0.223{col 90}{space 4}-.0434208{col 103}{space 3} .1836379
{txt}{space 44}100  {c |}{col 50}{res}{space 2} .1881469{col 62}{space 2} .2077214{col 73}{space 1}    0.91{col 82}{space 3}0.367{col 90}{space 4}-.2237723{col 103}{space 3} .6000662
{txt}{space 44}101  {c |}{col 50}{res}{space 2} .3812481{col 62}{space 2}  .165259{col 73}{space 1}    2.31{col 82}{space 3}0.023{col 90}{space 4} .0535333{col 103}{space 3} .7089629
{txt}{space 44}102  {c |}{col 50}{res}{space 2} .3113898{col 62}{space 2} .2103671{col 73}{space 1}    1.48{col 82}{space 3}0.142{col 90}{space 4}-.1057762{col 103}{space 3} .7285557
{txt}{space 44}103  {c |}{col 50}{res}{space 2} .0903359{col 62}{space 2} .1136824{col 73}{space 1}    0.79{col 82}{space 3}0.429{col 90}{space 4}-.1351006{col 103}{space 3} .3157724
{txt}{space 44}104  {c |}{col 50}{res}{space 2}-.1600684{col 62}{space 2} .0623926{col 73}{space 1}   -2.57{col 82}{space 3}0.012{col 90}{space 4}-.2837953{col 103}{space 3}-.0363416
{txt}{space 44}105  {c |}{col 50}{res}{space 2} .2518026{col 62}{space 2}  .198362{col 73}{space 1}    1.27{col 82}{space 3}0.207{col 90}{space 4}-.1415567{col 103}{space 3} .6451619
{txt}{space 48} {c |}
{space 44}year {c |}
{space 43}2011  {c |}{col 50}{res}{space 2}-.0011033{col 62}{space 2} .0036474{col 73}{space 1}   -0.30{col 82}{space 3}0.763{col 90}{space 4}-.0083361{col 103}{space 3} .0061296
{txt}{space 43}2012  {c |}{col 50}{res}{space 2} .0121949{col 62}{space 2} .0046997{col 73}{space 1}    2.59{col 82}{space 3}0.011{col 90}{space 4} .0028752{col 103}{space 3} .0215147
{txt}{space 43}2013  {c |}{col 50}{res}{space 2} .0147634{col 62}{space 2} .0059514{col 73}{space 1}    2.48{col 82}{space 3}0.015{col 90}{space 4} .0029615{col 103}{space 3} .0265653
{txt}{space 43}2014  {c |}{col 50}{res}{space 2} .0154809{col 62}{space 2} .0071227{col 73}{space 1}    2.17{col 82}{space 3}0.032{col 90}{space 4} .0013564{col 103}{space 3} .0296054
{txt}{space 43}2015  {c |}{col 50}{res}{space 2} .0099055{col 62}{space 2} .0088665{col 73}{space 1}    1.12{col 82}{space 3}0.266{col 90}{space 4}-.0076771{col 103}{space 3} .0274881
{txt}{space 43}2016  {c |}{col 50}{res}{space 2} .0087505{col 62}{space 2} .0085665{col 73}{space 1}    1.02{col 82}{space 3}0.309{col 90}{space 4}-.0082372{col 103}{space 3} .0257382
{txt}{space 43}2017  {c |}{col 50}{res}{space 2} .0137423{col 62}{space 2} .0132154{col 73}{space 1}    1.04{col 82}{space 3}0.301{col 90}{space 4}-.0124642{col 103}{space 3} .0399489
{txt}{space 43}2018  {c |}{col 50}{res}{space 2} -.013116{col 62}{space 2} .0121806{col 73}{space 1}   -1.08{col 82}{space 3}0.284{col 90}{space 4}-.0372707{col 103}{space 3} .0110386
{txt}{space 43}2019  {c |}{col 50}{res}{space 2}-.0442567{col 62}{space 2} .0131943{col 73}{space 1}   -3.35{col 82}{space 3}0.001{col 90}{space 4}-.0704216{col 103}{space 3}-.0180918
{txt}{space 48} {c |}
{space 43}_cons {c |}{col 50}{res}{space 2} .1497658{col 62}{space 2} .5142335{col 73}{space 1}    0.29{col 82}{space 3}0.771{col 90}{space 4}-.8699786{col 103}{space 3}  1.16951
{txt}{hline 49}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1984008{col 39} -1921987{col 50}    25{col 58}  3844024{col 69}  3844343
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. 
. ** BY NON-SUPERVISORS RESPONDENT: BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. lincom c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0604503{col 26}{space 2} .0358996{col 37}{space 1}    1.68{col 46}{space 3}0.095{col 54}{space 4}  -.01074{col 67}{space 3} .1316406
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority_het#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority_het#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0176347{col 26}{space 2} .0175638{col 37}{space 1}    1.00{col 46}{space 3}0.318{col 54}{space 4}-.0171951{col 67}{space 3} .0524644
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.minority_het#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.minority_het#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0533415{col 26}{space 2} .0248668{col 37}{space 1}    2.15{col 46}{space 3}0.034{col 54}{space 4} .0040296{col 67}{space 3} .1026534
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. lincom  2.minority_het#c.ln_ratio_mnmsup_mnmsub - 1.minority_het#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.minority_het#c.ln_ratio_mnmsup_mnmsub + 2.minority_het#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0357068{col 26}{space 2}  .018801{col 37}{space 1}    1.90{col 46}{space 3}0.060{col 54}{space 4}-.0015764{col 67}{space 3}   .07299
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *
. *
. *
. *
. *
. 
. 
. ** BY SUPERVISOR RESPONDENT: BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. lincom c.ln_ratio_mnmsup_mnmsub+ 1.supervisor#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_mnmsup_mnmsub + 1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0423804{col 26}{space 2} .0417314{col 37}{space 1}    1.02{col 46}{space 3}0.312{col 54}{space 4}-.0403746{col 67}{space 3} .1251353
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority_het#c.ln_ratio_mnmsup_mnmsub +  1.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority_het#c.ln_ratio_mnmsup_mnmsub + 1.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0664256{col 26}{space 2} .0176088{col 37}{space 1}    3.77{col 46}{space 3}0.000{col 54}{space 4} .0315068{col 67}{space 3} .1013445
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.minority_het#c.ln_ratio_mnmsup_mnmsub +  2.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.minority_het#c.ln_ratio_mnmsup_mnmsub + 2.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0656441{col 26}{space 2} .0222236{col 37}{space 1}    2.95{col 46}{space 3}0.004{col 54}{space 4} .0215739{col 67}{space 3} .1097143
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. lincom  2.minority_het#c.ln_ratio_mnmsup_mnmsub +  2.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub - (1.minority_het#c.ln_ratio_mnmsup_mnmsub +  1.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub)

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.minority_het#c.ln_ratio_mnmsup_mnmsub + 2.minority_het#c.ln_ratio_mnmsup_mnmsub - 1.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub + 2.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0007815{col 26}{space 2} .0266264{col 37}{space 1}   -0.03{col 46}{space 3}0.977{col 54}{space 4}-.0535826{col 67}{space 3} .0520195
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. 
. 
. * SUPERVISOR - NON-SUPERVISORY DIFFERENCE AMONG MINORITY RESPONDENT DIFFERENCES [MINORITY MEN RESPONDENTS FOLLOWED BY MINORITY WOMEN RESPONDENTS] -- DO NOT PLOT IN GRAPHS [ONLY FOR TEXT]!
. 
. lincom  1.minority_het#c.ln_ratio_mnmsup_mnmsub +  1.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub - (1.minority_het#c.ln_ratio_mnmsup_mnmsub)

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0487909{col 26}{space 2} .0134158{col 37}{space 1}    3.64{col 46}{space 3}0.000{col 54}{space 4} .0221868{col 67}{space 3} .0753951
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. lincom  2.minority_het#c.ln_ratio_mnmsup_mnmsub +  2.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub - (2.minority_het#c.ln_ratio_mnmsup_mnmsub)

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lnjustice2~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0123026{col 26}{space 2} .0344376{col 37}{space 1}    0.36{col 46}{space 3}0.722{col 54}{space 4}-.0559885{col 67}{space 3} .0805937
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. clear
{txt}
{com}. 
. *** FIGURE E1: PLOT ELASTICITY MARGINAL EFFECTS FOR MODELS E1 & E2 USING LINCOMS ABOVE FOR EACH MODEL: PATTERN AFTER COMPARABLE SET OF MANUSCRIPT GRAPHICS/FIGURES [FIGURE 1]
. 
. import excel "C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\figuree1.xlsx", sheet("Sheet1") firstrow
{res}{text}(5 vars, 8 obs)

{com}. destring, replace
{txt}row already numeric; no {res}replace
{txt}group already numeric; no {res}replace
{txt}estimates already numeric; no {res}replace
{txt}low95 already numeric; no {res}replace
{txt}high95 already numeric; no {res}replace
{txt}
{com}. 
. set scheme sj, permanently
{txt}({cmd:set scheme} preference recorded)

{com}. graph set window fontface "Century Schoolbook"
{txt}
{com}. 
. twoway (rcap low95 high95 row, vert) (scatter estimates row if group ==1, msymbol(square) mcolor(orange))(scatter estimates row if group ==2, msymbol(circle_hollow) mcolor(orange))(scatter estimates row if group ==3, msymbol(square) mcolor(navy))(scatter estimates row if group ==4, msymbol(circle_hollow) mcolor(navy)), legend(row(1) order(2 "Gender" 4 "Race/Ethnicity") pos(6)) title("FIGURE E1" "Relationship Between Authority Differentials and Organizational Justice Employee Evaluations" "(By Respondent Single Social Identity Group)", size(small)) ylabel(-0.1(.1)0.2, labsize (small) angle(horizon)) xtitle("AD Estimates [Differentials by Respondent Single Social Identity Group]" "(Models 1&2)", size(small)) xlabel("", noticks) yline(0, lpattern(dash) lcolor(gs8)) aspect(.5)
{res}{txt}
{com}. 
. clear
{txt}
{com}. 
. *** FIGURE E2: PLOT ELASTICITY MARGINAL EFFECTS FOR MODELS E3 & E4 USING LINCOMS ABOVE FOR EACH MODEL: PATTERN AFTER COMPARABLE SET OF MANUSCRIPT GRAPHICS/FIGURES [FIGURE 2]
. import excel "C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\figuree2.xlsx", sheet("Sheet1") firstrow
{res}{text}(10 vars, 12 obs)

{com}. destring, replace
{txt}row already numeric; no {res}replace
{txt}group already numeric; no {res}replace
{txt}estimates already numeric; no {res}replace
{txt}low95 already numeric; no {res}replace
{txt}high95 already numeric; no {res}replace
{txt}F already numeric; no {res}replace
{txt}G already numeric; no {res}replace
{txt}H already numeric; no {res}replace
{txt}I already numeric; no {res}replace
{txt}J already numeric; no {res}replace
{txt}
{com}. 
. set scheme sj, permanently 
{txt}({cmd:set scheme} preference recorded)

{com}. graph set window fontface "Century Schoolbook"
{txt}
{com}. 
. twoway (rcap low95 high95 row, vert) (scatter estimates row if group ==1, msymbol(square) mcolor(orange))(scatter estimates row if group ==2, msymbol(circle_hollow) mcolor(orange)) (scatter estimates row if group ==3, msymbol(diamond_hollow) mcolor(orange))(scatter estimates row if group ==4, msymbol(triangle_hollow) mcolor(orange))(scatter estimates row if group ==5, msymbol(square) mcolor(navy))(scatter estimates row if group ==6, msymbol(circle_hollow) mcolor(navy))(scatter estimates row if group ==7, msymbol(diamond_hollow) mcolor(navy))(scatter estimates row if group ==8, msymbol(triangle_hollow) mcolor(navy)), legend(row(1) order(2 "Gender" 6 "Race/Ethnicity") pos(6)) title("FIGURE E2"  "Relationship Between Authority Differentials and Organizational Justice Employee Evaluations" `"(By Respondent Intersectional Social Identity Group)"', size(medsmall)) ylabel(-0.1(.1)0.2, labsize (small) angle(horizon)) xtitle("Gender AD Effects: by Respondent Intersectionality Group   Race/Ethnicity AD Effects: by Respondent Intersectionality Group", size(vsmall)) xlabel("", noticks) yline(0, lpattern(dash) lcolor(gs8)) aspect(.5)
{res}{txt}
{com}. 
. clear
{txt}
{com}. 
. *** FIGURE E3: PLOT ELASTICITY MARGINAL EFFECTS FOR MODELS E5-E8 USING LINCOMS ABOVE FOR EACH MODEL: PATTERN AFTER COMPARABLE SET OF MANUSCRIPT GRAPHICS/FIGURES  --- NON-SUPERVISOR RESPONDENT ESTIMATES [FIGURE 3]
. import excel "C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\figuree3.xlsx", sheet("Sheet1") firstrow
{res}{text}(14 vars, 18 obs)

{com}. destring, replace
{txt}row already numeric; no {res}replace
{txt}group already numeric; no {res}replace
{txt}estimates already numeric; no {res}replace
{txt}low95 already numeric; no {res}replace
{txt}high95 already numeric; no {res}replace
{txt}F already numeric; no {res}replace
{txt}G already numeric; no {res}replace
{txt}H already numeric; no {res}replace
{txt}I already numeric; no {res}replace
{txt}J already numeric; no {res}replace
{txt}K already numeric; no {res}replace
{txt}L already numeric; no {res}replace
{txt}M already numeric; no {res}replace
{txt}N already numeric; no {res}replace
{txt}
{com}. 
. set scheme sj, permanently  
{txt}({cmd:set scheme} preference recorded)

{com}. graph set window fontface "Century Schoolbook"
{txt}
{com}. 
. twoway (rcap low95 high95 row, vert) (scatter estimates row if group ==1, msymbol(square) mcolor(orange))(scatter estimates row if group ==2, msymbol(square_hollow) mcolor(orange)) (scatter estimates row if group ==3, msymbol(square) mcolor(navy))(scatter estimates row if group ==4, msymbol(square_hollow) mcolor(navy))(scatter estimates row if group ==5, msymbol(square) mcolor(orange))(scatter estimates row if group ==6, msymbol(circle_hollow) mcolor(orange))(scatter estimates row if group ==7, msymbol(diamond_hollow) mcolor(orange))(scatter estimates row if group ==8, msymbol(triangle_hollow) mcolor(orange))(scatter estimates row if group ==9, msymbol(square) mcolor(navy))(scatter estimates row if group ==10, msymbol(circle_hollow) mcolor(navy))(scatter estimates row if group ==11, msymbol(diamond_hollow) mcolor(navy))(scatter estimates row if group ==12, msymbol(triangle_hollow) mcolor(navy)), legend(row(1) order(2 "Gender" 4 "Race/Ethnicity") pos(6)) title("FIGURE E3" "Relationship Between Authority Differentials and Organizational Justice Employee Evaluations" "(Non-Supervisory Respondents: Single and Intersectional Social Identity Groups)", size(medsmall)) ylabel(-0.1(.1)0.2, labsize (small) angle(horizon)) xtitle("AD Effects: by Respondent Single Identity Group        AD Effects: by Respondent Intersectionality Group", size(vsmall)) xlabel("", noticks) yline(0, lpattern(dash) lcolor(gs8)) aspect(.5)
{res}{txt}
{com}. 
. clear
{txt}
{com}. 
. *** FIGURE E4: PLOT ELASTICITY MARGINAL EFFECTS FOR MODELS E5-E8 USING LINCOMS ABOVE FOR EACH MODEL: PATTERN AFTER COMPARABLE SET OF MANUSCRIPT GRAPHICS/FIGURES --- SUPERVISOR RESPONDENT ESTIMATES [FIGURE 4] 
. import excel "C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\figuree4.xlsx", sheet("Sheet1") firstrow
{res}{text}(14 vars, 18 obs)

{com}. destring, replace
{txt}row already numeric; no {res}replace
{txt}group already numeric; no {res}replace
{txt}estimates already numeric; no {res}replace
{txt}low95 already numeric; no {res}replace
{txt}high95 already numeric; no {res}replace
{txt}F already numeric; no {res}replace
{txt}G already numeric; no {res}replace
{txt}H already numeric; no {res}replace
{txt}I already numeric; no {res}replace
{txt}J already numeric; no {res}replace
{txt}K already numeric; no {res}replace
{txt}L already numeric; no {res}replace
{txt}M already numeric; no {res}replace
{txt}N already numeric; no {res}replace
{txt}
{com}. 
. set scheme sj, permanently 
{txt}({cmd:set scheme} preference recorded)

{com}. graph set window fontface "Century Schoolbook"
{txt}
{com}. 
. twoway (rcap low95 high95 row, vert) (scatter estimates row if group ==1, msymbol(square) mcolor(orange))(scatter estimates row if group ==2, msymbol(square_hollow) mcolor(orange)) (scatter estimates row if group ==3, msymbol(square) mcolor(navy))(scatter estimates row if group ==4, msymbol(square_hollow) mcolor(navy))(scatter estimates row if group ==5, msymbol(square) mcolor(orange))(scatter estimates row if group ==6, msymbol(circle_hollow) mcolor(orange))(scatter estimates row if group ==7, msymbol(diamond_hollow) mcolor(orange))(scatter estimates row if group ==8, msymbol(triangle_hollow) mcolor(orange))(scatter estimates row if group ==9, msymbol(square) mcolor(navy))(scatter estimates row if group ==10, msymbol(circle_hollow) mcolor(navy))(scatter estimates row if group ==11, msymbol(diamond_hollow) mcolor(navy))(scatter estimates row if group ==12, msymbol(triangle_hollow) mcolor(navy)), legend(row(1) order(2 "Gender" 4 "Race/Ethnicity") pos(6)) title("FIGURE E4" "Relationship Between Authority Differentials and Organizational Justice Employee Evaluations" "(Supervisor Respondents: Single and Intersectional Social Identity Groups)", size(small)) ylabel(-0.1(.1)0.3, labsize (small) angle(horizon)) xtitle("AD Effects: by Respondent Single Identity Group       AD Effects: by Respondent Intersectionality Group", size(vsmall)) xlabel("", noticks) yline(0, lpattern(dash) lcolor(gs8)) aspect(.5)
{res}{txt}
{com}. 
. 
. ******************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
.    
. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\Krause & Park.Authority Differentials.APPENDIX E RESULTS.08-07-2024.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 7 Aug 2024, 15:50:51
{txt}{.-}
{smcl}
{txt}{sf}{ul off}